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Статті в журналах з теми "Semantics of word-forming base"
1
Zalavina, Tatyana Yu, Ludmila I. Antropova, Liliya S. Polyakova, and Yulia V. Yuzhakova. "SOMATIC PHRASEOLOGICAL UNITS WITH A COMMON NEGATIVE CONNOTATION IN NATIONAL LANGUAGES (BASED ON FRENCH)." Theoretical and Applied Linguistics, no. 2 (2019): 18–27. http://dx.doi.org/10.22250/24107190_2019_5_2_18_27.
Повний текст джерелаАнотація:
This work reports the results of the study of the meaning of somatic phraseological units with negative connotations in the French language within the anthropocentric paradigm. We emphasize active character of forming somatic phraseological units characterized by the two-dimensional semantic structure. To compare the semantics of variable word combinations and the corresponding phraseological units the analysis of primary transposition results was used to map the semantics of variable word combinations and phraseological units - a method typically applied for such a purpose; another method used was the application of an idiom onto the corresponding variable word combination to determine the degree of the components semantic merging to create coherent meaning of the studied idioms. As a result of the analysis of French somatic phraseological units, we singled out a set of words belonging to the semantic field of negative meanings that express various feelings and are used to characterize actions or people.
2
Danilina, Natalia I. "COGNITIVE POTENTIAL OF VERBS OF SPEECH (on the Material of the Latin Language)." Вестник Пермского университета. Российская и зарубежная филология 12, no. 3 (2020): 15–23. http://dx.doi.org/10.17072/2073-6681-2020-3-15-23.
Повний текст джерелаАнотація:
Тhe article aims to identify and compare the specific cognitive potential of prototypical verbs dicere, loqui, fari in the Latin language of the classical period, to determine its origins. Objects of analysis are semantic variants of the verbs and their derivatives. The research methods include semantic, cognitive, etymological analysis. The cognitive potential of a word family is determined by the etymological semantics of the base word. In the dicere word family, the semantics of speaking is secondary and develops in interaction with the etymological meaning ‘to show’. In some of the subfamilies, this meaning is implemented exclusively; members of these subfamilies represent social realities of the legal sphere. In the word family, there are many derivatives with mental or voluntary components of semantics dominating. The loqui word family stems from the base with the meaning ‘to make a sound’. It is dominated by derivatives with the meaning of speaking, speech is primarily revealed as a means of interpersonal contact. The etymological semantics of the verb fari combines the semantics of speaking with the idea of transpersonal nature of speech. As a result, some derivatives characterize speech as a process, others are concentrated in the cognitive sphere of the cult. The former direction is supported by secondary cognitive spheres associated with the unofficial use of speech (‘Rumor’, ‘Folklore’), the latter direction generates secondary cognitive spheres in which speech is interpreted as a means of communication between a person and higher powers (‘Fate’) or the state (‘Law’). The word families in question have areas of cognitive intersection: ‘Eloquence’ in loqui and fari (actualization of the semantics of speaking), ‘Speech as a means of regulating social relations’ in dicere and fari (actualization of voluntary components of semantics and the idea of transpersonal nature of speech).
3
Charitonidis, Chariton. "Colour verbs in Modern Greek: A cognitive approach." Word Structure 7, no. 2 (October 2014): 125–52. http://dx.doi.org/10.3366/word.2014.0063.
Повний текст джерелаАнотація:
This paper gives an outlook on how the coordination between phonology and semantics in verb derivation may look, and which constraints the distinction between possible/established, possible/novel, and not possible/forced verbs can be mapped onto. The object of investigation are the colour -ízo verbs in Modern Greek. The analysis is mainly based on the studies by Berlin & Kay (1969) , Kay & McDaniel (1978) , and Kay & Maffi (1999) on basic colour terms. The colour verbs in Modern Greek are compared with the English colour verbs. It is shown that systematic gaps linked to the causative/inchoative paradigm of -ízo verbs are due to the semantics of the base rather than deficiencies in the base's morphophonological character. The lower the evolutional stage that a base can be fitted to, the more likely an -ízo derivative will be produced.
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Prokopуeva, Aleksandra Egorovna. "The formation of intransitive verbs from the base of quality processes in Kolyma dialect of the Yukaghir language." Филология: научные исследования, no. 11 (November 2020): 120–28. http://dx.doi.org/10.7256/2454-0749.2020.11.34201.
Повний текст джерелаАнотація:
The subject of this article is the intransitive verbs in Kolyma dialect of the Yukaghir language. In Yukaghir linguistics does not feature special research on the verb word formation of this dialect, which defines the relevance of this work. The object of this article is the affixes used for the formation of intransitive verbs from the base of quality processes (qualitives). The goal of this article is to describe the formation of intransitive verbs from the base of quality processes of Kolyma dialect of the Yukaghir language, as well as to clarify the meanings of word-forming affixes. The scientific novelty consists in the analysis and description of the formation of intransitive verbs from the base of quality verbs of the language of wood Yukaghir folk. The results lies in determination and specification of the semantics of word-forming affixes of intransitive verbs, formed from the base of qualitaty processes, such as -mu (reducing to various changes), -kie (acquisition of a certain quality or transition from one state to another), -ba ~ - ge, - lye, - d (completed action or process), - buo (semi imposition of a quality), - de and the suffix of one-time action – s’ - (completed action or process).
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Greshchuk, Vasyl’. "Slovotvirne hnizdo z vershynoyu Khrystos u movniy kartyni svitu ukrayintsiv." Studia Ucrainica Varsoviensia, no. 8 (August 31, 2020): 11–19. http://dx.doi.org/10.31338/2299-7237suv.8.6.
Повний текст джерелаАнотація:
The article discusses the example of a word-formative nest with the apex of Christ. It analyses the role of word-formation in the formation of the language picture of the world of Ukrainians. The word-formative nest fi xes the word-forming segment of the semantic space of the Christ concept of the sacred conceptual sphere. Despite the fact that the anthroponomies as vertices of word-formation nests do not exhibit derivational productivity in the Ukrainian language, the word-formation nest with the apex of Christ has a branched structure: in the three stages of derivation, 25 derivatives of diff erent parts of the language, created in diff erent ways, have been certifi ed. This is due to the semantics of the vertex word of the nest, the importance of the concept named by it, in the perception of Ukrainians, in their culture of belief. In the linguistic consciousness of Ukrainians, Christ – Jesus Christ, the Son of God, the God-man, the incarnate God, the Savior, the Teacher, the Creator of the new religion. Such a broad semantic spectrum determines the activation of the derivation possibilities of the base word and the verbalization of word-formative means by a number of conceptual components. An analysis of the word-formative nest with the apex of Christ has shown that the word-formative dimension in the language picture of the world of Ukrainians, along with the universal conceptual components inherent in many diverse Christians, also has a number of individual-language derivational means of categorizing the world.
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Koriakowcewa, Elena, Larisa Ratsiburskaya, and Marina Sandakova. "Intensifiers in the Language of the 21st Century: Word-Building, Semantics, Syntagmatics and Dynamics of Evalution." Vestnik Volgogradskogo gosudarstvennogo universiteta. Serija 2. Jazykoznanije, no. 5 (January 2022): 6–19. http://dx.doi.org/10.15688/jvolsu2.2021.5.1.
Повний текст джерелаАнотація:
The article considers the categories of evaluation and intensity in cognitive and pragmatic aspects. The purpose of the research is to establish the relationship between the categories of evaluation and intensity based on the material of word-building and lexical-semantic units from lexicographic sources and media and fiction texts. As a result of the research, word-building and lexical-semantic intensifiers are characterized by the use of word-building, semantic and contextual methods. The article shows such kinds of intensifiers as affixes and affixoides in neoderivatives, neoderivatives created on the base of reduplication. The article shows the estimated ambivalence of dimensional-evaluative affixes, in connection with pragmatic conditions, context and semantics of productive base. The article describes such an extension of the functional range of intensifiers as oxymoron quality and ambivalence of lexical intensifiers. The functions of the intensifiers (pragmatic and stylistic) are defined. The repeatability of syntagmatic bias models indicates the dynamics of evaluation in the class of lexical intensifiers in the Russian language of the modern period. The phenomena described in the article generally show the development of the semantic category of intensity in the Russian language of the 21 st century, which is expressed in the dynamics of its components, such as word-building means, word-building units, lexical units.
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KOLESOVA, IRINA E. "FORMING WORD CLUSTERS BASED ON VERBS WITH THE SEMANTICS ‘SOUNDING’ IN THE DIALECT OF BORBUSHINO VILLAGE." Cherepovets State University Bulletin 1, no. 106 (2022): 119–26. http://dx.doi.org/10.23859/1994-0637-2022-1-106-10.
Повний текст джерелаАнотація:
The article examines the peculiarities of verbal word-forming clusters, which are included in the lexico-semantic field ‘sounding’ in the dialect of Borbushino village, Kirillovsky district of Vologda region. The author considers their components and structure, gives examples of word-formation models characteristic of this lexico-semantic field. The features of the verbal word formation in the Borbushin dialect are described within the general context of the speech culture of historical Belozerye and the system of Vologda dialects as a whole.
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Liu, Ling, and Sang-Bing Tsai. "Intelligent Recognition and Teaching of English Fuzzy Texts Based on Fuzzy Computing and Big Data." Wireless Communications and Mobile Computing 2021 (July 10, 2021): 1–10. http://dx.doi.org/10.1155/2021/1170622.
Повний текст джерелаАнотація:
In this paper, we conduct in-depth research and analysis on the intelligent recognition and teaching of English fuzzy text through parallel projection and region expansion. Multisense Soft Cluster Vector (MSCVec), a multisense word vector model based on nonnegative matrix decomposition and sparse soft clustering, is constructed. The MSCVec model is a monolingual word vector model, which uses nonnegative matrix decomposition of positive point mutual information between words and contexts to extract low-rank expressions of mixed semantics of multisense words and then uses sparse. It uses the nonnegative matrix decomposition of the positive pointwise mutual information between words and contexts to extract the low-rank expressions of the mixed semantics of the polysemous words and then uses the sparse soft clustering algorithm to partition the multiple word senses of the polysemous words and also obtains the global sense of the polysemous word affiliation distribution; the specific polysemous word cluster classes are determined based on the negative mean log-likelihood of the global affiliation between the contextual semantics and the polysemous words, and finally, the polysemous word vectors are learned using the Fast text model under the extended dictionary word set. The advantage of the MSCVec model is that it is an unsupervised learning process without any knowledge base, and the substring representation in the model ensures the generation of unregistered word vectors; in addition, the global affiliation of the MSCVec model can also expect polysemantic word vectors to single word vectors. Compared with the traditional static word vectors, MSCVec shows excellent results in both word similarity and downstream text classification task experiments. The two sets of features are then fused and extended into new semantic features, and similarity classification experiments and stack generalization experiments are designed for comparison. In the cross-lingual sentence-level similarity detection task, SCLVec cross-lingual word vector lexical-level features outperform MSCVec multisense word vector features as the input embedding layer; deep semantic sentence-level features trained by twin recurrent neural networks outperform the semantic features of twin convolutional neural networks; extensions of traditional statistical features can effectively improve cross-lingual similarity detection performance, especially cross-lingual topic model (BL-LDA); the stack generalization integration approach maximizes the error rate of the underlying classifier and improves the detection accuracy.
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Bilousova, Viktoria V., and Raisa V. Kelembet. "COMPOSITIONAL SEMANTICS OF THE COMPLEX LANGUAGE FACTS WITH THE ENGLISH -ING FORMANT (on the material of Ukrainian)." Alfred Nobel University Journal of Philology 2, no. 22 (2021): 122–30. http://dx.doi.org/10.32342/2523-4463-2021-2-22-10.
Повний текст джерелаАнотація:
The article focuses on the problems of formal and semantically complex English borrowings analyzed through the prism of cognitive linguistics and with applying its methodological set of approaches. The authors aimed at making an attempt of systematizing the compositional semantics of the complex language facts and determining their derivative character. This intention is realized through the task to identify the mechanism of transferring the word-building meanings to the recipient language where they gain their new meaning and motivation. It is a general fact that compositional semantics of the derivative word in the donor language is built on the evident language facts (base + formant), they possess their own peculiarities of formal and semantic complex and their own motivated character. They determined the choice of the research methods such as comparative, structural, descriptive and typological approaches applying in our work. In this study we try to determine the import of every borrowed word component into its resulted integrative meaning. Cognitive linguistics is directly related with the process of language processing inside our mind and describes the mechanism of its reflecting and producing into the human speech. This is the reason to apply its tools and develop them in aspect of compositional semantics especially in terms of word formation that we use for proving the facts of transporting the word-building meaning that is contained in a formal and semantic borrowed word complex. Inside the recipient language such a complex opens its word-building abilities including their categories in system of words. The borrowed formal and semantic word complex has to be considered from the different sides and not only on the lexical and thematic level or morphemic and grammatical level but also on the word-building one. The borrowed words of this type should be analyzed on the derivative level too, because it is a derivative complex accepted as a part of speech and formant -ing on some stages of assimilation are considered as word-building element. According to the results of research we proved that any language fact is activated in a process of realization its communicative task and then it uses its formal, semantic and creative tools for expressing “new meaning”. The authors’ idea is that the meaning of derivative words (including borrowed words) is derived in a motivated way from the meanings of their components as well as their form and their semantics. It is resulted by the number of formal and semantic similar borrowings that belong to one word-building range. It is motivated by their word components. The speaker understands this type of word because of its special meaning and pronunciation and reflects it in one’s subjective creative language world. This approach for analysis of borrowed language facts let us formulate the following conclusion: creative reflection of the formal and semantic complex of the borrowed words presented as a complex, not a simplex in a speaker’s mind. This complex contains a formant with determined word-building meaning, in our work it is the transliterated English borrowing with -ing formant into Ukrainian.
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Janz, Arkadiusz, and Maciej Piasecki. "A Weakly supervised word sense disambiguation for Polish using rich lexical resources." Poznan Studies in Contemporary Linguistics 55, no. 2 (June 26, 2019): 339–65. http://dx.doi.org/10.1515/psicl-2019-0013.
Повний текст джерелаАнотація:
Abstract Automatic word sense disambiguation (WSD) has proven to be an important technique in many natural language processing tasks. For many years the problem of sense disambiguation has been approached with a wide range of methods, however, it is still a challenging problem, especially in the unsupervised setting. One of the well-known and successful approaches to WSD are knowledge-based methods leveraging lexical knowledge resources such as wordnets. As the knowledge-based approaches mostly do not use any labelled training data their performance strongly relies on the structure and the quality of used knowledge sources. However, a pure knowledge-base such as a wordnet cannot reflect all the semantic knowledge necessary to correctly disambiguate word senses in text. In this paper we explore various expansions to plWordNet as knowledge-bases for WSD. Semantic links extracted from a large valency lexicon (Walenty), glosses and usage examples, Wikipedia articles and SUMO ontology are combined with plWordNet and tested in a PageRank-based WSD algorithm. In addition, we analyse also the influence of lexical semantics vector models extracted with the help of the distributional semantics methods. Several new Polish test data sets for WSD are also introduced. All the resources, methods and tools are available on open licences.
Дисертації з теми "Semantics of word-forming base"
1
Sinha, Ravi Som. "Graph-based Centrality Algorithms for Unsupervised Word Sense Disambiguation." Thesis, University of North Texas, 2008. https://digital.library.unt.edu/ark:/67531/metadc9736/.
Повний текст джерелаАнотація:
This thesis introduces an innovative methodology of combining some traditional dictionary based approaches to word sense disambiguation (semantic similarity measures and overlap of word glosses, both based on WordNet) with some graph-based centrality methods, namely the degree of the vertices, Pagerank, closeness, and betweenness. The approach is completely unsupervised, and is based on creating graphs for the words to be disambiguated. We experiment with several possible combinations of the semantic similarity measures as the first stage in our experiments. The next stage attempts to score individual vertices in the graphs previously created based on several graph connectivity measures. During the final stage, several voting schemes are applied on the results obtained from the different centrality algorithms. The most important contributions of this work are not only that it is a novel approach and it works well, but also that it has great potential in overcoming the new-knowledge-acquisition bottleneck which has apparently brought research in supervised WSD as an explicit application to a plateau. The type of research reported in this thesis, which does not require manually annotated data, holds promise of a lot of new and interesting things, and our work is one of the first steps, despite being a small one, in this direction. The complete system is built and tested on standard benchmarks, and is comparable with work done on graph-based word sense disambiguation as well as lexical chains. The evaluation indicates that the right combination of the above mentioned metrics can be used to develop an unsupervised disambiguation engine as powerful as the state-of-the-art in WSD.
2
Grover, Ishaan. "A semantics based computational model for word learning." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120694.
Повний текст джерелаАнотація:
Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 73-77).
Studies have shown that children's early literacy skills can impact their ability to achieve academic success, attain higher education and secure employment later in life. However, lack of resources and limited access to educational content causes a "knowledge gap" between children that come from different socio-economic backgrounds. To solve this problem, there has been a recent surge in the development of Intelligent Tutoring Systems (ITS) to provide learning benefits to children. However, before providing new content, an ITS must assess a child's existing knowledge. Several studies have shown that children learn new words by forming semantic relationships with words they already know. Human tutors often implicitly use semantics to assess a tutee's word knowledge from partial and noisy data. In this thesis, I present a cognitively inspired model that uses word semantics (semantics-based model) to make inferences about a child's vocabulary from partial information about their existing vocabulary. Using data from a one-to-one learning intervention between a robotic tutor and 59 children, I show that the proposed semantics-based model outperforms (on average) models that do not use word semantics (semantics-free models). A subject level analysis of results reveals that different models perform well for different children, thus motivating the need to combine predictions. To this end, I present two methods to combine predictions from semantics-based and semantics-free models and show that these methods yield better predictions of a child's vocabulary knowledge. Finally, I present an application of the semantics-based model to evaluate if a learning intervention was successful in teaching children new words while enhancing their semantic understanding. More concretely, I show that a personalized word learning intervention with a robotic tutor is better suited to enhance children's vocabulary when compared to a non-personalized intervention. These results motivate the use of semantics-based models to assess children's knowledge and build ITS that maximize children's semantic understanding of words.
"This research was supported by NSF IIP-1717362 and NSF IIS-1523118"--Page 10.
by Ishaan Grover.
S.M.
3
Burton, Marilyn Elizabeth. "Semantics of glory : a cognitive, corpus-based approach to Hebrew word meaning." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/9573.
Повний текст джерелаАнотація:
The concept of ‘glory’ is one of the most significant themes in the Hebrew Bible, lying at the heart of God’s self-disclosure in biblical revelation. Yet, while the concept has received theological treatment, and while various relevant Hebrew roots have individually benefited from linguistic survey, the group of lexemes surrounding this concept is as yet untouched by a comprehensive semantic study. Through indepth semantic study this thesis offers a clearer understanding of the interrelations and differences between the Classical Hebrew lexemes centring around the concept of ‘glory’. The first chapter opens with a critical examination of both structuralist and cognitivist approaches to semantic research, focussing particularly on their historical use and current applicability to the study of ancient languages. It outlines the superior claims of cognitive semantics accurately to model patterns of language usage, addressing the challenges inherent in the application of such an approach to ancient language. The proposed methodology is characterised as cognitive in nature, focussed on both lexical interrelations (relational) and the internal composition of lexemes (decompositional), exhaustive in relating lexemes to each other point by point, and based on the entirety of the Classical Hebrew corpus. Finally, this chapter discusses issues relating to the limited, diachronic and fragmentary nature of the Classical Hebrew corpus. The second chapter delineates the boundaries of the semantic domain of כבוד . It opens with a methodological discussion introducing parallel terms and word pairs as valuable tools in the objective identification of semantically related terms. Proposing the theory that members of a semantic domain will regularly co-occur, it systematically analyses firstly the extant word associations of כבוד itself and secondly of those lexemes recurring in association with it, accepting or rejecting each as a member of its semantic domain on the basis of word associations. This process results in the identification of eleven lexemes as members of the semantic domain of The concept of ‘glory’ is one of the most significant themes in the Hebrew Bible, lying at the heart of God’s self-disclosure in biblical revelation. Yet, while the concept has received theological treatment, and while various relevant Hebrew roots have individually benefited from linguistic survey, the group of lexemes surrounding this concept is as yet untouched by a comprehensive semantic study. Through indepth semantic study this thesis offers a clearer understanding of the interrelations and differences between the Classical Hebrew lexemes centring around the concept of ‘glory’. The first chapter opens with a critical examination of both structuralist and cognitivist approaches to semantic research, focussing particularly on their historical use and current applicability to the study of ancient languages. It outlines the superior claims of cognitive semantics accurately to model patterns of language usage, addressing the challenges inherent in the application of such an approach to ancient language. The proposed methodology is characterised as cognitive in nature, focussed on both lexical interrelations (relational) and the internal composition of lexemes (decompositional), exhaustive in relating lexemes to each other point by point, and based on the entirety of the Classical Hebrew corpus. Finally, this chapter discusses issues relating to the limited, diachronic and fragmentary nature of the Classical Hebrew corpus. The second chapter delineates the boundaries of the semantic domain of כבוד . It opens with a methodological discussion introducing parallel terms and word pairs as valuable tools in the objective identification of semantically related terms. Proposing the theory that members of a semantic domain will regularly co-occur, it systematically analyses firstly the extant word associations of כבוד itself and secondly of those lexemes recurring in association with it, accepting or rejecting each as a member of its semantic domain on the basis of word associations. This process results in the identification of eleven lexemes as members of the semantic domain of The concept of ‘glory’ is one of the most significant themes in the Hebrew Bible, lying at the heart of God’s self-disclosure in biblical revelation. Yet, while the concept has received theological treatment, and while various relevant Hebrew roots have individually benefited from linguistic survey, the group of lexemes surrounding this concept is as yet untouched by a comprehensive semantic study. Through indepth semantic study this thesis offers a clearer understanding of the interrelations and differences between the Classical Hebrew lexemes centring around the concept of ‘glory’. The first chapter opens with a critical examination of both structuralist and cognitivist approaches to semantic research, focussing particularly on their historical use and current applicability to the study of ancient languages. It outlines the superior claims of cognitive semantics accurately to model patterns of language usage, addressing the challenges inherent in the application of such an approach to ancient language. The proposed methodology is characterised as cognitive in nature, focussed on both lexical interrelations (relational) and the internal composition of lexemes (decompositional), exhaustive in relating lexemes to each other point by point, and based on the entirety of the Classical Hebrew corpus. Finally, this chapter discusses issues relating to the limited, diachronic and fragmentary nature of the Classical Hebrew corpus. The second chapter delineates the boundaries of the semantic domain of כבוד . It opens with a methodological discussion introducing parallel terms and word pairs as valuable tools in the objective identification of semantically related terms. Proposing the theory that members of a semantic domain will regularly co-occur, it systematically analyses firstly the extant word associations of כבוד itself and secondly of those lexemes recurring in association with it, accepting or rejecting each as a member of its semantic domain on the basis of word associations. This process results in the identification of eleven lexemes as members of the semantic domain of כבוד.
4
Sinha, Ravi Som Mihalcea Rada F. "Graph-based centrality algorithms for unsupervised word sense disambiguation." [Denton, Tex.] : University of North Texas, 2008. http://digital.library.unt.edu/permalink/meta-dc-9736.
Повний текст джерела
5
Esin, Yunus Emre. "Improvement Of Corpus-based Semantic Word Similarity Using Vector Space Model." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12610759/index.pdf.
Повний текст джерелаАнотація:
This study presents a new approach for finding semantically similar words from corpora using
window based context methods. Previous studies mainly concentrate on either finding
new combination of distance-weight measurement methods or proposing new context methods.
The main difference of this new approach is that this study reprocesses the outputs of
the existing methods to update the representation of related word vectors used for measuring
semantic distance between words, to improve the results further. Moreover, this novel technique
provides a solution to the data sparseness of vectors which is a common problem in
methods which uses vector space model.
The main advantage of this new approach is that it is applicable to many of the existing word
similarity methods using the vector space model. The other and the most important advantage
of this approach is that it improves the performance of some of these existing word similarity
measuring methods.
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Manion, Steve Lawrence. "Unsupervised Knowledge-based Word Sense Disambiguation: Exploration & Evaluation of Semantic Subgraphs." Thesis, University of Canterbury. Department of Mathematics & Statistics, 2014. http://hdl.handle.net/10092/10016.
Повний текст джерелаАнотація:
Hypothetically, if you were told: Apple uses the apple as its logo . You would
immediately detect two different senses of the word apple , these being the
company and the fruit respectively. Making this distinction is the formidable
challenge of Word Sense Disambiguation (WSD), which is the subtask of
many Natural Language Processing (NLP) applications. This thesis is a
multi-branched investigation into WSD, that explores and evaluates unsupervised
knowledge-based methods that exploit semantic subgraphs. The
nature of research covered by this thesis can be broken down to:
1. Mining data from the encyclopedic resource Wikipedia, to visually
prove the existence of context embedded in semantic subgraphs
2. Achieving disambiguation in order to merge concepts that originate
from heterogeneous semantic graphs
3. Participation in international evaluations of WSD across a range of
languages
4. Treating WSD as a classification task, that can be optimised through
the iterative construction of semantic subgraphs
The contributions of each chapter are ranged, but can be summarised by
what has been produced, learnt, and raised throughout the thesis. Furthermore
an API and several resources have been developed as a by-product
of this research, all of which can be accessed by visiting the author’s home
page at http://www.stevemanion.com. This should enable researchers to
replicate the results achieved in this thesis and build on them if they wish.
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Lilliehöök, Hampus. "Extraction of word senses from bilingual resources using graph-based semantic mirroring." Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-91880.
Повний текст джерелаАнотація:
In this thesis we retrieve semantic information that exists implicitly in bilingual data. We gather input data by repeatedly applying the semantic mirroring procedure. The data is then represented by vectors in a large vector space. A resource of synonym clusters is then constructed by performing K-means centroid-based clustering on the vectors. We evaluate the result manually, using dictionaries, and against WordNet, and discuss prospects and applications of this method.I det här arbetet utvinner vi semantisk information som existerar implicit i tvåspråkig data. Vi samlar indata genom att upprepa proceduren semantisk spegling. Datan representeras som vektorer i en stor vektorrymd. Vi bygger sedan en resurs med synonymkluster genom att applicera K-means-algoritmen på vektorerna. Vi granskar resultatet för hand med hjälp av ordböcker, och mot WordNet, och diskuterar möjligheter och tillämpningar för metoden.
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Milajevs, Dmitrijs. "A study of model parameters for scaling up word to sentence similarity tasks in distributional semantics." Thesis, Queen Mary, University of London, 2018. http://qmro.qmul.ac.uk/xmlui/handle/123456789/36225.
Повний текст джерелаАнотація:
Representation of sentences that captures semantics is an essential part of natural language processing systems, such as information retrieval or machine translation. The representation of a sentence is commonly built by combining the representations of the words that the sentence consists of. Similarity between words is widely used as a proxy to evaluate semantic representations. Word similarity models are well-studied and are shown to positively correlate with human similarity judgements. Current evaluation of models of sentential similarity builds on the results obtained in lexical experiments. The main focus is how the lexical representations are used, rather than what they should be. It is often assumed that the optimal representations for word similarity are also optimal for sentence similarity. This work discards this assumption and systematically looks for lexical representations that are optimal for similarity measurement between sentences. We find that the best representation for word similarity is not always the best for sentence similarity and vice versa. The best models in word similarity tasks perform best with additive composition. However, the best result on compositional tasks is achieved with Kroneckerbased composition. There are representations that are equally good in both tasks when used with multiplicative composition. The systematic study of the parameters of similarity models reveals that the more information lexical representations contain, the more attention should be paid to noise. In particular, the word vectors in models with the feature size at the magnitude of the vocabulary size should be sparse, but if a small number of context features is used then the vectors should be dense. Given the right lexical representations, compositional operators achieve state-of-the-art performance, improving over models that use neural-word embeddings. To avoid overfitting, either several test datasets should be used or parameter selection should be based on parameters' average behaviours.
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Islam, Md Aminul. "Applications of corpus-based semantic similarity and word segmentation to database schema matching." Thesis, University of Ottawa (Canada), 2006. http://hdl.handle.net/10393/27256.
Повний текст джерелаАнотація:
In this thesis, we present a method for database schema matching, the problem of identifying elements of two given schemas that correspond to each other. Schema matching is useful in e-commerce exchanges, in data integration/warehousing, and in Semantic Web applications. We first present two corpus-based methods: one method is for determining the semantic similarity of two target words and the other is for automatic word segmentation. Then we present a name-based element-level database schema matching method that exploits both the semantic similarity and the word segmentation methods. Our word similarity method uses Pointwise Mutual Information (PMI) to sort lists of important neighbor words of the two target words and distinguish the words which are common in both lists and aggregate their PMI values (from the opposite list) to calculate the relative similarity score. Our word segmentation method uses corpus type frequency information to choose the type with maximum length and frequency from "desegmented" text. It also uses a modified forward-backward matching technique using maximum length frequency and entropy rate if any non-matching portions of the text exist. For the database schema matching method, we also use normalized and modified versions of the Longest Common Subsequence (LCS) string matching algorithm with weight factors to allow for a balanced combination. We validate our methods with experimental studies, the results of which suggest that these methods can be a useful addition to the set of existing methods.
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Stigeborn, Olivia. "Text ranking based on semantic meaning of sentences." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-300442.
Повний текст джерелаАнотація:
Finding a suitable candidate to client match is an important part of consultant companies work. It takes a lot of time and effort for the recruiters at the company to read possibly hundreds of resumes to find a suitable candidate. Natural language processing is capable of performing a ranking task where the goal is to rank the resumes with the most suitable candidates ranked the highest. This ensures that the recruiters are only required to look at the top ranked resumes and can quickly get candidates out in the field. Former research has used methods that count specific keywords in resumes and can make decisions on whether a candidate has an experience or not. The main goal of this thesis is to use the semantic meaning of the text in the resumes to get a deeper understanding of a candidate’s level of experience. It also evaluates if the model is possible to run on-device and if the database can contain a mix of English and Swedish resumes. An algorithm was created that uses the word embedding model DistilRoBERTa that is capable of capturing the semantic meaning of text. The algorithm was evaluated by generating job descriptions from the resumes by creating a summary of each resume. The run time, memory usage and the ranking the wanted candidate achieved was documented and used to analyze the results. When the candidate who was used to generate the job description is ranked in the top 10 the classification was considered to be correct. The accuracy was calculated using this method and an accuracy of 68.3% was achieved. The results show that the algorithm is capable of ranking resumes. The algorithm is able to rank both Swedish and English resumes with an accuracy of 67.7% for Swedish resumes and 74.7% for English. The run time was fast enough at an average of 578 ms but the memory usage was too large to make it possible to use the algorithm on-device. In conclusion the semantic meaning of resumes can be used to rank resumes and possible future work would be to combine this method with a method that counts keywords to research if the accuracy would increase.Att hitta en lämplig kandidat till kundmatchning är en viktig del av ett konsultföretags arbete. Det tar mycket tid och ansträngning för rekryterare på företaget att läsa eventuellt hundratals CV:n för att hitta en lämplig kandidat. Det finns språkteknologiska metoder för att rangordna CV:n med de mest lämpliga kandidaterna rankade högst. Detta säkerställer att rekryterare endast behöver titta på de topprankade CV:erna och snabbt kan få kandidater ut i fältet. Tidigare forskning har använt metoder som räknar specifika nyckelord i ett CV och är kapabla att avgöra om en kandidat har specifika erfarenheter. Huvudmålet med denna avhandling är att använda den semantiska innebörden av texten iCV:n för att få en djupare förståelse för en kandidats erfarenhetsnivå. Den utvärderar också om modellen kan köras på mobila enheter och om algoritmen kan rangordna CV:n oberoende av om CV:erna är på svenska eller engelska. En algoritm skapades som använder ordinbäddningsmodellen DistilRoBERTa som är kapabel att fånga textens semantiska betydelse. Algoritmen utvärderades genom att generera jobbeskrivningar från CV:n genom att skapa en sammanfattning av varje CV. Körtiden, minnesanvändningen och rankningen som den önskade kandidaten fick dokumenterades och användes för att analysera resultatet. När den kandidat som användes för att generera jobbeskrivningen rankades i topp 10 ansågs klassificeringen vara korrekt. Noggrannheten beräknades med denna metod och en noggrannhet på 68,3 % uppnåddes. Resultaten visar att algoritmen kan rangordna CV:n. Algoritmen kan rangordna både svenska och engelska CV:n med en noggrannhet på 67,7 % för svenska och 74,7 % för engelska. Körtiden var i genomsnitt 578 ms vilket skulle möjliggöra att algoritmen kan köras på mobila enheter men minnesanvändningen var för stor. Sammanfattningsvis kan den semantiska betydelsen av CV:n användas för att rangordna CV:n och ett eventuellt framtida arbete är att kombinera denna metod med en metod som räknar nyckelord för att undersöka hur noggrannheten skulle påverkas.
Книги з теми "Semantics of word-forming base"
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Schmid, Annemarie. Mettre à toutes les sauces: Analyse sémantico-syntaxique des lexies complexes à base de "mettre". [Metz]: Centre d'analyse syntaxique, Université de Metz, Faculté des lettres et sciences humaines, 1992.
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Papegaaij, Bart C. Word expert semantics: An interlingual knowledge-based approach. Dordrecht: Foris, 1986.
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Bavaeva, Ol'ga. Metaphorical parallels of the neutral nomination "man" in modern English. ru: INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1858259.
Повний текст джерелаАнотація:
The monograph is devoted to a multidimensional analysis of metaphor in modern English as a parallel nomination that exists along with a neutral equivalent denoting a person. The problem of determining the essence of metaphorical names and their role in the language has attracted the attention of many foreign and domestic linguists on the material of various languages, but until now the fact of the parallel existence of metaphors and neutral nominations has not been emphasized.
The research is in line with modern problems of linguistics related to the relationship of language, thinking and reflection of the surrounding reality. All these problems are integrated and resolved within the framework of linguistic semantics, in particular in the semantics of metaphor. Multilevel study of language material based on semantic, component, etymological analysis methods contributed to a systematic and comprehensive description of this most important part of the lexical system of the English language.
Metaphorical parallels are considered as the result of the interaction of three complexes, which allows us to identify their associative-figurative base, as well as the types of metaphorical parallels, depending on the nature of the connection between direct and figurative meaning. Based on the analysis of various human character traits and behavior that evoke associations with animals, birds, objects, zoomorphic, artifact, somatic, floral and anthropomorphic metaphorical parallels of the neutral nomination "man" are distinguished. The social aspect of metaphorical parallels is also investigated as a reflection of gender, status and age characteristics of a person.
It can be used in the training of philologists and translators when reading theoretical courses on lexicology, stylistics, word formation of the English language, as well as in practical classes, in lexicographic practice.
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Sokolova, Elena. Onomastic space of monuments of writing of Kievan Rus. ru: INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1869553.
Повний текст джерелаАнотація:
The monograph is devoted to the problem of recreating the linguistic-ethnic unity of the Old Russian anthroponymic and toponymic systems, the discovery of direct connections between the proper name and mental landmarks.
The monograph provides a comprehensive description of the onomasticon of ancient Russian monuments of writing in line with comparative historical linguistics, taking into account the encyclopedic, ethnolinguistic and etymological characteristics of proper names. The system and structure of the onomastic space of monuments of ecclesiastical and secular content of the XI-XIII centuries are investigated, conceptual approaches to their description are proposed. The study of the functions of proper names, their morphemics and semantics allowed us to establish the national and cultural specifics of the Old Russian onomastic vocabulary, to determine the prospects for its evolution, as well as the formation of the modern Russian anthroponymic system.
Modeling of the Old Russian onomastic space both in the field of anthroponymy and toponymy takes into account the connection of proper names with contextual usage. The participation of nominal signs in the formation of the space of written and artistic texts of the era of the Kievan state is based on the attachment of certain proper names to texts of a religious and secular nature. Nomination in the space of proper names is considered in the monograph not only as a process of activity of a creative nature, but also as a means of onymic word production in the older era.
It is addressed to specialists in historical lexicology and onomastics, language history, teachers of literature, local historians.
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Dressler, Wolfgang U., and Lavinia Merlini Barbaresi. Pragmatics and Morphology. Edited by Yan Huang. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199697960.013.20.
Повний текст джерелаАнотація:
Within a theory of morphopragmatics, we give an account of the relationship between morphology and pragmatics starting from two major theoretical premises: first, that pragmatics is not a secondary meaning derived from semantics—on the contrary we assume a priority of pragmatics over semantics—and second, that morphology is capable of a direct interface with pragmatics, not mediated through its semantics. Thus certain morphological patterns may generate autonomous pragmatic meanings, independently of their denotative power. Eligible patterns are primarily evaluative affixes (diminutives, augmentatives, pejoratives), familiarizers, like French -o, and hypocoristics, whose effects extend from the pertinent base word to the entire speech act. Other morphological elements, such as for example the Japanese honorific -masu and the Germanic and Hungarian excessive, limit their pragmatic scope to the word base. Some other morphological patterns are more marginal, for example feminine motional suffixes or pluralis maiestatis.
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Word expert semantics: An interlingual knowledge-based approach. Dordrecht: Foris Publications, 1986.
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Papegaaij, Bart C. Word Expert Semantics: An Interlingual Knowledge-Based Approach. De Gruyter, Inc., 2019.
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Word Expert Semantics: An Interlingual Knowledge-Based Approach. Mouton De Gruyter, 1986.
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Papegaaij, Bart C. Word Expert Semantics: An Interlingual Knowledge-Based Approach. Foris Pubns USA, 1986.
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Glanville, Peter John. Words, roots, and patterns. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198792734.003.0002.
Повний текст джерелаАнотація:
Chapter 2 establishes the semantic makeup of word meaning in general, dividing it into semantic structure and conceptual content. It familiarizes the reader with roots and patterns in Arabic morphology, investigating the semantic abstractions discernable in sets of words that share a root, in addition to the semantic structure shared by words formed in the same pattern. The chapter introduces the notion of shape-invariant morphology, arriving at an approach to Arabic morphology in which some derivation is rule-based, with operations being carried out directly on base words, whereas another type of derivation involves root extraction from a source word. Word patterns are created when a morphological operation is carried out on a base word with some regularity. Once the pattern exists, a variety of base words can be mapped to it by root extraction, creating a uniform output regardless of the shape of the input word.
Частини книг з теми "Semantics of word-forming base"
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Degemmis, M., P. Lops, and G. Semeraro. "WordNet-Based Word Sense Disambiguation for Learning User Profiles." In Semantics, Web and Mining, 18–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11908678_2.
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ten Haaf, Fenna, Christopher Claassen, Ruben Eschauzier, Joanne Tjan, Daniël Buijs, Flavius Frasincar, and Kim Schouten. "WEB-SOBA: Word Embeddings-Based Semi-automatic Ontology Building for Aspect-Based Sentiment Classification." In The Semantic Web, 340–55. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77385-4_20.
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Hristea, Florentina T. "Semantic WordNet-Based Feature Selection." In The Naïve Bayes Model for Unsupervised Word Sense Disambiguation, 17–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33693-5_3.
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Jagoda, Jakub, and Tomasz Boiński. "Assessing Word Difficulty for Quiz-Like Game." In Semantic Keyword-Based Search on Structured Data Sources, 70–79. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74497-1_7.
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Sun, Maosong, Shengfen Luo, and Benjamin K. T’sou. "Word Extraction Based on Semantic Constraints in Chinese Word-Formation." In Computational Linguistics and Intelligent Text Processing, 202–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-30586-6_20.
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Zuo, Xin, Huanhuan Hu, Weiming Zhang, and Nenghai Yu. "Text Semantic Steganalysis Based on Word Embedding." In Cloud Computing and Security, 485–95. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00015-8_42.
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Sha, Yun, Ming Xia, Huina Jiang, and Xiaohua Wang. "Word Semantic Orientation Calculation Algorithm Based on Dynamic Standard Word Set." In Advances in Intelligent and Soft Computing, 125–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28314-7_18.
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Li, Changliang, Teng Ma, Yujun Zhou, Jian Cheng, and Bo Xu. "Measuring Word Semantic Similarity Based on Transferred Vectors." In Neural Information Processing, 326–35. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70093-9_34.
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Li, Xiaoli, Jimin Liu, and Zhongzhi Shi. "A Document Classifier Based on Word Semantic Association." In PRICAI 2000 Topics in Artificial Intelligence, 824. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44533-1_113.
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Liao, Xuanyi, and Guang Cheng. "Analysing the Semantic Change Based on Word Embedding." In Natural Language Understanding and Intelligent Applications, 213–23. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-50496-4_18.
Повний текст джерелаТези доповідей конференцій з теми "Semantics of word-forming base"
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Grover, Ishaan, Hae Won Park, and Cynthia Breazeal. "A Semantics-based Model for Predicting Children's Vocabulary." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/188.
Повний текст джерелаАнотація:
Intelligent tutoring systems (ITS) provide educational benefits through one-on-one tutoring by assessing children's existing knowledge and providing tailored educational content. In the domain of language acquisition, several studies have shown that children often learn new words by forming semantic relationships with words they already know. In this paper, we present a model that uses word semantics (semantics-based model) to make inferences about a child's vocabulary from partial information about their existing vocabulary knowledge. We show that the proposed semantics-based model outperforms models that do not use word semantics (semantics-free models) on average. A subject-level analysis of results reveals that different models perform well for different children, thus motivating the need to combine predictions. To this end, we use two methods to combine predictions from semantics-based and semantics-free models and show that these methods yield better predictions of a child's vocabulary knowledge. Our results motivate the use of semantics-based models to assess children's vocabulary knowledge and build ITS that maximizes children's semantic understanding of words.
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Mazumder, Sahisnu, and Bing Liu. "Context-aware Path Ranking for Knowledge Base Completion." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/166.
Повний текст джерелаАнотація:
Knowledge base (KB) completion aims to infer missing facts from existing ones in a KB. Among various approaches, path ranking (PR) algorithms have received increasing attention in recent years. PR algorithms enumerate paths between entity-pairs in a KB and use those paths as features to train a model for missing fact prediction. Due to their good performances and high model interpretability, several methods have been proposed. However, most existing methods suffer from scalability (high RAM consumption) and feature explosion (trains on an exponentially large number of features) problems. This paper proposes a Context-aware Path Ranking (C-PR) algorithm to solve these problems by introducing a selective path exploration strategy. C-PR learns global semantics of entities in the KB using word embedding and leverages the knowledge of entity semantics to enumerate contextually relevant paths using bidirectional random walk. Experimental results on three large KBs show that the path features (fewer in number) discovered by C-PR not only improve predictive performance but also are more interpretable than existing baselines.
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Suzen, Neslihan, Alexander N. Gorban, Jeremy Levesley, and Evgeny M. Mirkes. "An Informational Space based Semantic Analysis for Scientific Texts." In 10th International Conference on Foundations of Computer Science & Technology (FCST 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.120807.
Повний текст джерелаАнотація:
One major problem in Natural Language Processing is the automatic analysis and representation of human language. Human language is ambiguous and deeper understanding of semantics and creating human-to-machine interaction have required an effort in creating the schemes for act of communication and building common-sense knowledge bases for the ‘meaning’ in texts. This paper introduces computational methods for semantic analysis and the quantifying the meaning of short scientific texts. Computational methods extracting semantic feature are used to analyse the relations between texts of messages and ‘representations of situations’ for a newly created large collection of scientific texts, Leicester Scientific Corpus. The representation of scientific-specific meaning is standardised by replacing the situation representations, rather than psychological properties, with the vectors of some attributes: a list of scientific subject categories that the text belongs to. First, this paper introduces ‘Meaning Space’ in which the informational representation of the meaning is extracted from the occurrence of the word in texts across the scientific categories, i.e., the meaning of a word is represented by a vector of Relative Information Gain about the subject categories. Then, the meaning space is statistically analysed for Leicester Scientific Dictionary-Core and we investigate ‘Principal Components of the Meaning’ to describe the adequate dimensions of the meaning. The research in this paper conducts the base for the geometric representation of the meaning of texts.
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Shmelev, A. D. "LANGUAGE-SPECIFIC WORDS IN THE LIGHT OF TRANSLATION: THE RUSSIAN TOSKA." In International Conference on Computational Linguistics and Intellectual Technologies "Dialogue". Russian State University for the Humanities, 2020. http://dx.doi.org/10.28995/2075-7182-2020-19-658-669.
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This paper presents a semantic analysis of the most language-specific Russian word for ‘sadness’, namely, toska. The analysis is based on the hypothesis that one may regard translation equivalents and paraphrases of a linguistic unit extracted from real translated texts as a source of information about its semantics. The appearance of language-specific words in translated texts may be even more useful for studying their semantics. It turns out that тоска is not all that rare in Russian translated texts. The study of the incentives that lead Russian translators to use the word тоска often reveals important aspects of the semantics of this word. Stimuli for the appearance of toska in translations into Russian vary greatly. In general, when the original describes some bad feelings, the word toska appears if the original speaks of a subject’s unsatisfied desire, which desire may be vague and not well understood an
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Jiang, Xiaoze, Jing Yu, Yajing Sun, Zengchang Qin, Zihao Zhu, Yue Hu, and Qi Wu. "DAM: Deliberation, Abandon and Memory Networks for Generating Detailed and Non-repetitive Responses in Visual Dialogue." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/96.
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Visual Dialogue task requires an agent to be engaged in a conversation with human about an image. The ability of generating detailed and non-repetitive responses is crucial for the agent to achieve human-like conversation. In this paper, we propose a novel generative decoding architecture to generate high-quality responses, which moves away from decoding the whole encoded semantics towards the design that advocates both transparency and flexibility. In this architecture, word generation is decomposed into a series of attention-based information selection steps, performed by the novel recurrent Deliberation, Abandon and Memory (DAM) module. Each DAM module performs an adaptive combination of the response-level semantics captured from the encoder and the word-level semantics specifically selected for generating each word. Therefore, the responses contain more detailed and non-repetitive descriptions while maintaining the semantic accuracy. Furthermore, DAM is flexible to cooperate with existing visual dialogue encoders and adaptive to the encoder structures by constraining the information selection mode in DAM. We apply DAM to three typical encoders and verify the performance on the VisDial v1.0 dataset. Experimental results show that the proposed models achieve new state-of-the-art performance with high-quality responses. The code is available at https://github.com/JXZe/DAM.
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Maximova, Olga, and Tatiana Maykova. "PROPER NAMES AS TERMINOLOGY IN SOCIAL SCIENCE." In NORDSCI Conference Proceedings. Saima Consult Ltd, 2021. http://dx.doi.org/10.32008/nordsci2021/b1/v4/20.
Повний текст джерелаАнотація:
Proper names reflect the interaction between society and language. They identify unique entities and are used to refer to them. At the same time, it is not uncommon of proper names to serve as a source for word-formation. It should be noted, however, that while in a natural language (notably English) proper names mostly give rise to denominal verbs or adjectives, terminologies are different. Most units that count as terms are nouns, which makes their semantics somewhat special. The paper originates as one of a series towards a typology of sociological terminology and endeavors to analyze the terms whose etymology refers to a proper name (that is, eponymic terms). The research poses the following questions: whether this type of terms is common in Social Science, what are their structural and semantic distinctions as well as mechanisms behind their motivation, whether they are culture specific. The terms were manually retrieved from a set of data of 2500 terminological units extracted from a number of dictionaries and other sources. They were further grouped by structural criteria and the nature of eponymous components and made subject to morphological and semantic analyses. The research shows that structurally eponymic terms are morphological derivatives or two-(or more)-word compounds, with their prevalence estimated at 2%. The authors come to conclusion that terms of this type feature substantial diversity with regard to their eponymous components; they are motivated through the combination of encyclopedic knowledge of the entity, represented by the eponym, and the semantics of derivational morphemes or appellative components. Mythology-based eponymous terminology is represented by two groups, the first tracing back to Antiquity or biblical tradition, and the second of later origin, which requires a specific cultural experience for the meaning to be retrieved. Further analysis shows that the latter type along with toponym-based terminology is culture-specific in relation to American culture.
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Detkova, J., V. Novitskiy, M. Petrova, and V. Selegey. "DIFFERENTIAL SEMANTIC SKETCHES FOR RUSSIAN INTERNET-CORPORA." In International Conference on Computational Linguistics and Intellectual Technologies "Dialogue". Russian State University for the Humanities, 2020. http://dx.doi.org/10.28995/2075-7182-2020-19-211-227.
Повний текст джерелаАнотація:
The current paper suggests a new representation type of word collocations—the semantic sketches. It was first tested on one of the subcorpora of the General Internet-Corpus of Russian. The semantic sketches continue the idea of word sketches based on grammatical relations between words and expand it by adding the semantic information—word meanings and semantic relations between words. Moreover, the sketches can be additionally provided with metatextual characteristics. Certainly, building such sketches demands the semantic markup of the corpora. Therefore, we have used partial semantic analysis of the Compreno parser for our purposes. The paper demonstrates the examples of the sketches, provides the quality evaluation of the markup they are based on, and shows the advantages and disadvantages of the given approach.
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Xie, Ruobing, Xingchi Yuan, Zhiyuan Liu, and Maosong Sun. "Lexical Sememe Prediction via Word Embeddings and Matrix Factorization." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/587.
Повний текст джерелаАнотація:
Sememes are defined as the minimum semantic units of human languages. People have manually annotated lexical sememes for words and form linguistic knowledge bases. However, manual construction is time-consuming and labor-intensive, with significant annotation inconsistency and noise. In this paper, we for the first time explore to automatically predict lexical sememes based on semantic meanings of words encoded by word embeddings. Moreover, we apply matrix factorization to learn semantic relations between sememes and words. In experiments, we take a real-world sememe knowledge base HowNet for training and evaluation, and the results reveal the effectiveness of our method for lexical sememe prediction. Our method will be of great use for annotation verification of existing noisy sememe knowledge bases and annotation suggestion of new words and phrases.
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Meng, Fanqing, Wenpeng Lu, Yuteng Zhang, Ping Jian, Shumin Shi, and Heyan Huang. "QLUT at SemEval-2017 Task 2: Word Similarity Based on Word Embedding and Knowledge Base." In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017). Stroudsburg, PA, USA: Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/s17-2036.
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Xu, Jin, Yubo Tao, and Hai Lin. "Semantic word cloud generation based on word embeddings." In 2016 IEEE Pacific Visualization Symposium (PacificVis). IEEE, 2016. http://dx.doi.org/10.1109/pacificvis.2016.7465278.
Повний текст джерелаЗвіти організацій з теми "Semantics of word-forming base"
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Pikilnyak, Andrey V., Nadia M. Stetsenko, Volodymyr P. Stetsenko, Tetiana V. Bondarenko, and Halyna V. Tkachuk. Comparative analysis of online dictionaries in the context of the digital transformation of education. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4431.
Повний текст джерелаАнотація:
The article is devoted to a comparative analysis of popular online dictionaries and an overview of the main tools of these resources to study a language. The use of dictionaries in learning a foreign language is an important step to understanding the language. The effectiveness of this process increases with the use of online dictionaries, which have a lot of tools for improving the educational process. Based on the Alexa Internet resource it was found the most popular online dictionaries: Cambridge Dictionary, Wordreference, Merriam–Webster, Wiktionary, TheFreeDictionary, Dictionary.com, Glosbe, Collins Dictionary, Longman Dictionary, Oxford Dictionary. As a result of the deep analysis of these online dictionaries, we found out they have the next standard functions like the word explanations, transcription, audio pronounce, semantic connections, and examples of use. In propose dictionaries, we also found out the additional tools of learning foreign languages (mostly English) that can be effective. In general, we described sixteen functions of the online platforms for learning that can be useful in learning a foreign language. We have compiled a comparison table based on the next functions: machine translation, multilingualism, a video of pronunciation, an image of a word, discussion, collaborative edit, the rank of words, hints, learning tools, thesaurus, paid services, sharing content, hyperlinks in a definition, registration, lists of words, mobile version, etc. Based on the additional tools of online dictionaries we created a diagram that shows the functionality of analyzed platforms.
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Yatsymirska, Mariya. SOCIAL EXPRESSION IN MULTIMEDIA TEXTS. Ivan Franko National University of Lviv, February 2021. http://dx.doi.org/10.30970/vjo.2021.49.11072.
Повний текст джерелаАнотація:
The article investigates functional techniques of extralinguistic expression in multimedia texts; the effectiveness of figurative expressions as a reaction to modern events in Ukraine and their influence on the formation of public opinion is shown. Publications of journalists, broadcasts of media resonators, experts, public figures, politicians, readers are analyzed. The language of the media plays a key role in shaping the worldview of the young political elite in the first place. The essence of each statement is a focused thought that reacts to events in the world or in one’s own country. The most popular platform for mass information and social interaction is, first of all, network journalism, which is characterized by mobility and unlimited time and space. Authors have complete freedom to express their views in direct language, including their own word formation. Phonetic, lexical, phraseological and stylistic means of speech create expression of the text. A figurative word, a good aphorism or proverb, a paraphrased expression, etc. enhance the effectiveness of a multimedia text. This is especially important for headlines that simultaneously inform and influence the views of millions of readers. Given the wide range of issues raised by the Internet as a medium, research in this area is interdisciplinary. The science of information, combining language and social communication, is at the forefront of global interactions. The Internet is an effective source of knowledge and a forum for free thought. Nonlinear texts (hypertexts) – «branching texts or texts that perform actions on request», multimedia texts change the principles of information collection, storage and dissemination, involving billions of readers in the discussion of global issues. Mastering the word is not an easy task if the author of the publication is not well-read, is not deep in the topic, does not know the psychology of the audience for which he writes. Therefore, the study of media broadcasting is an important component of the professional training of future journalists. The functions of the language of the media require the authors to make the right statements and convincing arguments in the text. Journalism education is not only knowledge of imperative and dispositive norms, but also apodictic ones. In practice, this means that there are rules in media creativity that are based on logical necessity. Apodicticity is the first sign of impressive language on the platform of print or electronic media. Social expression is a combination of creative abilities and linguistic competencies that a journalist realizes in his activity. Creative self-expression is realized in a set of many important factors in the media: the choice of topic, convincing arguments, logical presentation of ideas and deep philological education. Linguistic art, in contrast to painting, music, sculpture, accumulates all visual, auditory, tactile and empathic sensations in a universal sign – the word. The choice of the word for the reproduction of sensory and semantic meanings, its competent use in the appropriate context distinguishes the journalist-intellectual from other participants in forums, round tables, analytical or entertainment programs. Expressive speech in the media is a product of the intellect (ability to think) of all those who write on socio-political or economic topics. In the same plane with him – intelligence (awareness, prudence), the first sign of which (according to Ivan Ogienko) is a good knowledge of the language. Intellectual language is an important means of organizing a journalistic text. It, on the one hand, logically conveys the author’s thoughts, and on the other – encourages the reader to reflect and comprehend what is read. The richness of language is accumulated through continuous self-education and interesting communication. Studies of social expression as an important factor influencing the formation of public consciousness should open up new facets of rational and emotional media broadcasting; to trace physical and psychological reactions to communicative mimicry in the media. Speech mimicry as one of the methods of disguise is increasingly becoming a dangerous factor in manipulating the media. Mimicry is an unprincipled adaptation to the surrounding social conditions; one of the most famous examples of an animal characterized by mimicry (change of protective color and shape) is a chameleon. In a figurative sense, chameleons are called adaptive journalists. Observations show that mimicry in politics is to some extent a kind of game that, like every game, is always conditional and artificial.