Relevant bibliographies by topics / Generic sentence

Academic literature on the topic 'Generic sentence'

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Published: 11 March 2023

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Journal articles on the topic "Generic sentence"

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MILLER, MEGAN M., and LORI E. JAMES. "Is the generic pronoun he still comprehended as excluding women?" American Journal of Psychology 122, no. 4 (December 1, 2009): 483–96. http://dx.doi.org/10.2307/27784423.

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Abstract We investigated whether the use of he as a generic masculine (GM) pronoun affects comprehension. Participants read sentences containing GM or sex-specific pronouns and indicated whether each sentence could refer to a female. GM sentences were less accurately interpreted than sex-specific sentences, indicating that the sex-specific function of masculine pronouns dominates in comprehension. We also varied sentence antecedents, and participants made fewer errors on sentences with predominantly female than predominantly male or neutral antecedents. In another experiment, we tested male and female participants under conditions of time pressure. Participants of both sexes evidenced the error pattern of Experiment 1. Findings support the hypothesis that GM pronouns reduce the likelihood of thoughts of females in what are intended to be non–sex-specific instances.
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Vanetik, Natalia, and Marina Litvak. "Definition Extraction from Generic and Mathematical Domains with Deep Ensemble Learning." Mathematics 9, no. 19 (October 6, 2021): 2502. http://dx.doi.org/10.3390/math9192502.

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Definitions are extremely important for efficient learning of new materials. In particular, mathematical definitions are necessary for understanding mathematics-related areas. Automated extraction of definitions could be very useful for automated indexing educational materials, building taxonomies of relevant concepts, and more. For definitions that are contained within a single sentence, this problem can be viewed as a binary classification of sentences into definitions and non-definitions. In this paper, we focus on automatic detection of one-sentence definitions in mathematical and general texts. We experiment with different classification models arranged in an ensemble and applied to a sentence representation containing syntactic and semantic information, to classify sentences. Our ensemble model is applied to the data adjusted with oversampling. Our experiments demonstrate the superiority of our approach over state-of-the-art methods in both general and mathematical domains.
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Dief, Nada A., Ali E. Al-Desouky, Amr Aly Eldin, and Asmaa M. El-Said. "An Adaptive Semantic Descriptive Model for Multi-Document Representation to Enhance Generic Summarization." International Journal of Software Engineering and Knowledge Engineering 27, no. 01 (February 2017): 23–48. http://dx.doi.org/10.1142/s0218194017500024.

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Due to the increasing accessibility of online data and the availability of thousands of documents on the Internet, it becomes very difficult for a human to review and analyze each document manually. The sheer size of such documents and data presents a significant challenge for users. Providing automatic summaries of specific topics helps the users to overcome this problem. Most of the current extractive multi-document summarization systems can successfully extract summary sentences; however, many limitations exist which include the degree of redundancy, inaccurate extraction of important sentences, low coverage and poor coherence among the selected sentences. This paper introduces an adaptive extractive multi-document generic (EMDG) methodology for automatic text summarization. The framework of this methodology relies on a novel approach for sentence similarity measure, a discriminative sentence selection method for sentence scoring and a reordering technique for the extracted sentences after removing the redundant ones. Extensive experiments are done on the summarization benchmark datasets DUC2005, DUC2006 and DUC2007. This proves that the proposed EMDG methodology is more effective than the current extractive multi-document summarization systems. Rouge evaluation for automatic summarization is used to validate the proposed EMDG methodology, and the experimental results showed that it is more effective and outperforms the baseline techniques, where the generated summary is characterized by high coverage and cohesion.
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Fedorenko, Evelina, Terri L. Scott, Peter Brunner, William G. Coon, Brianna Pritchett, Gerwin Schalk, and Nancy Kanwisher. "Neural correlate of the construction of sentence meaning." Proceedings of the National Academy of Sciences 113, no. 41 (September 26, 2016): E6256—E6262. http://dx.doi.org/10.1073/pnas.1612132113.

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The neural processes that underlie your ability to read and understand this sentence are unknown. Sentence comprehension occurs very rapidly, and can only be understood at a mechanistic level by discovering the precise sequence of underlying computational and neural events. However, we have no continuous and online neural measure of sentence processing with high spatial and temporal resolution. Here we report just such a measure: intracranial recordings from the surface of the human brain show that neural activity, indexed by γ-power, increases monotonically over the course of a sentence as people read it. This steady increase in activity is absent when people read and remember nonword-lists, despite the higher cognitive demand entailed, ruling out accounts in terms of generic attention, working memory, and cognitive load. Response increases are lower for sentence structure without meaning (“Jabberwocky” sentences) and word meaning without sentence structure (word-lists), showing that this effect is not explained by responses to syntax or word meaning alone. Instead, the full effect is found only for sentences, implicating compositional processes of sentence understanding, a striking and unique feature of human language not shared with animal communication systems. This work opens up new avenues for investigating the sequence of neural events that underlie the construction of linguistic meaning.
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Yadav, Chandra Shekhar, and Aditi Sharan. "Hybrid Approach for Single Text Document Summarization Using Statistical and Sentiment Features." International Journal of Information Retrieval Research 5, no. 4 (October 2015): 46–70. http://dx.doi.org/10.4018/ijirr.2015100104.

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Summarization is a way to represent same information in concise way with equal sense. This can be categorized in two type Abstractive and Extractive type. Our work is focused around Extractive summarization. A generic approach to extractive summarization is to consider sentence as an entity, score each sentence based on some indicative features to ascertain the quality of sentence for inclusion in summary. Sort the sentences on the score and consider top n sentences for summarization. Mostly statistical features have been used for scoring the sentences. A hybrid model for a single text document summarization is being proposed. This hybrid model is an extraction based approach, which is combination of Statistical and semantic technique. The hybrid model depends on the linear combination of statistical measures: sentence position, TF-IDF, Aggregate similarity, centroid, and semantic measure. The idea to include sentiment analysis for salient sentence extraction is derived from the concept that emotion plays an important role in communication to effectively convey any message hence, it can play a vital role in text document summarization. For comparison, five system summaries have been generated: Proposed Work, MEAD system, Microsoft system, OPINOSIS system, and Human generated summary, and evaluation is done using ROUGE score.
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곽은주. "A Pseudo Characterizing Generic Sentence in Korean." Korean Journal of Linguistics 32, no. 1 (March 2007): 1–25. http://dx.doi.org/10.18855/lisoko.2007.32.1.001.

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Isonuma, Masaru, Junichiro Mori, Danushka Bollegala, and Ichiro Sakata. "Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance." Transactions of the Association for Computational Linguistics 9 (2021): 945–61. http://dx.doi.org/10.1162/tacl_a_00406.

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Abstract This paper presents a novel unsupervised abstractive summarization method for opinionated texts. While the basic variational autoencoder-based models assume a unimodal Gaussian prior for the latent code of sentences, we alternate it with a recursive Gaussian mixture, where each mixture component corresponds to the latent code of a topic sentence and is mixed by a tree-structured topic distribution. By decoding each Gaussian component, we generate sentences with tree-structured topic guidance, where the root sentence conveys generic content, and the leaf sentences describe specific topics. Experimental results demonstrate that the generated topic sentences are appropriate as a summary of opinionated texts, which are more informative and cover more input contents than those generated by the recent unsupervised summarization model (Bražinskas et al., 2020). Furthermore, we demonstrate that the variance of latent Gaussians represents the granularity of sentences, analogous to Gaussian word embedding (Vilnis and McCallum, 2015).
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Bojar, Ondřej, and Kateřina Veselovská. "Resources for Indonesian Sentiment Analysis." Prague Bulletin of Mathematical Linguistics 103, no. 1 (April 1, 2015): 21–41. http://dx.doi.org/10.1515/pralin-2015-0002.

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Abstract In this work, we present subjectivity lexicons of positive and negative expressions for Indonesian language created by automatically translating English lexicons. Other variations are created by intersecting or unioning them. We compare the lexicons in the task of predicting sentence polarity on a set of 446 manually annotated sentences and we also contrast the generic lexicons with a small lexicon extracted directly from the annotated sentences (in a cross-validation setting). We seek for further improvements by assigning weights to lexicon entries and by wrapping the prediction into a machine learning task with a small number of additional features. We observe that lexicons are able to reach high recall but suffer from low precision when predicting whether a sentence is evaluative (positive or negative) or not (neutral). Weighting the lexicons can improve either the recall or the precision but with a comparable decrease in the other measure.
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김윤신. "Semantics and Classification of the Korean Generic Passive Sentence." EONEOHAG ll, no. 68 (April 2014): 197–217. http://dx.doi.org/10.17290/jlsk.2014..68.197.

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Hojaee Cheon. "On the Generic Sentence and Middle Construction in Japanese." Journal of Japanese Language and Literature 63, no. 1 (November 2007): 551–70. http://dx.doi.org/10.17003/jllak.2007.63.1.551.

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Dissertations / Theses on the topic "Generic sentence"

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Oliveira, Marco Antonio Perez de. "A coisa julgada sobre a sentença genérica coletiva." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/2/2137/tde-07062013-080415/.

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A dissertação se ocupa da análise da coisa julgada sobre a sentença genérica coletiva de procedência que, segundo a regra do artigo 95 do Código de Defesa do Consumidor brasileiro, tem por objeto a fixação de responsabilidade do réu para efeitos da tutela coletiva de direitos individuais homogêneos. O primeiro capítulo analisa a ação civil coletiva do direito brasileiro, com particular ênfase para a repartição da atividade cognitiva entre as questões comuns, objeto da ação coletiva propriamente dita, e das questões particulares que constituem objeto das ações complementares em que se apuram a titularidade e o conteúdo dos direitos individuais a cuja tutela se direciona o procedimento. O capítulo seguinte realiza uma revisão da teoria da coisa julgada, sob a ótica da vinculação da jurisdição moderna à tutela dos direitos previamente reconhecidos pela ordem jurídica, que passam a constituir a unidade mínima estrutural do processo civil. Finalmente, o último capítulo classifica a sentença genérica coletiva como modalidade de sentença parcial de mérito e examina diferentes teorias que buscaram explicar a estabilidade desse tipo de decisão. Os resultados atingidos são aplicados para se estudar a viabilidade do estabelecimento de parâmetros de liquidação na própria sentença genérica e a obrigatoriedade das questões resolvidas pela sentença genérica em ações conexas à ação coletiva
This dissertation deals with the analysis of the effects of res judicata upon the generic collective sentence which, according to article 95 of Brazilian Consumers Defense Code, has for object the fixation of defendants liability in the context of collective redress of individual rights. First Chapter analyses the civil collective action in Brazilian law, emphasizing the bifurcation of procedure that separates the decision of common issues, which are tried in the collective suit; and of particular issues, that constitute the object of complementary suits in which are tried the ownership and contents of individual claims. The following Chapter reviews the theory of res judicata in civil procedure, under the perspective of modern jurisdictions function of protection of rights previously recognized by law, making them the minimal structural unit of civil procedure. Finally, the last Chapter classifies the generic collective sentence as a species of partial sentence on the merits, and reviews different theories that tried to explain the stability of this sort of decision in order to identify its defining features. The results achieved are applied in the study of admissibility of claim-value definition in the very generic collective sentence, as well as in the binding effect of the common issue resolution in parallel suits.
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Seal, Amy. "Scoring sentences developmentally : an analog of developmental sentence scoring /." Diss., CLICK HERE for online access:, 2001. http://contentdm.lib.byu.edu/ETD/image/etd12.pdf.

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Veysey, Christopher Lawrence. "Syntactic complexity and sentence processing." Thesis, University of Cambridge, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.708578.

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Finney, Mianisha C. "Simulating Specific Language Impairment: Effects of Sentence Length and Input Rate on Complex Sentence Comprehension." Ohio : Ohio University, 2009. http://www.ohiolink.edu/etd/view.cgi?ohiou1255023751.

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Phillips, Jacquelyn Louise. "Sentence complexity and variation in school texts /." [St. Lucia, Qld.], 2005. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18878.pdf.

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Myachykov, Andriy. "Integrating perceptual, semantic and syntactic information in sentence production." Thesis, Connect to e-thesis. Move to record for print version, 2007. http://theses.gla.ac.uk/31/.

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Thesis (Ph.D.) - University of Glasgow, 2007.
Ph.D. thesis submitted to the Department of Psychology, Faculty of Law, Business and Social Sciences, University of Glasgow, 2007. Includes bibliographical references. Print version also available.
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Judson, Carrie Ann. "Accuracy of Automated Developmental Sentence Scoring Software." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1448.pdf.

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Hillard, Dustin Lundring. "Automatic sentence structure annotation for spoken language processing /." Thesis, Connect to this title online; UW restricted, 2008. http://hdl.handle.net/1773/6080.

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Peterson, Justin. "Making novelty normal : a theory of sentence processing." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/8241.

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Boberg, Per. "Word by word, phrase by phrase, sentence by sentence : A corpus-based study of the N1 by N1 construction." Thesis, Växjö universitet, Institutionen för humaniora, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-5771.

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The present paper examines the N1 by N1 construction using corpus linguistic methodology.The distribution of types of the construction that occur more than once either unhyphenated or hyphenated in any subcorpus of the British National Corpus accessed through the BrighamYoung University interface is examined. Written and spoken language as well as variousgenres are compared. Hyphenation is also investigated. A collocation analysis of some typesof the construction is further carried out and it is concluded that the N1 by N1 construction canbe part of the on a N1 by N1 basis construction. Results from the quantitative analysis as wellas the qualitative discussion suggest that the N P N construction may be undergoinglexicalisation starting as an adverbial and moving to functioning as a premodifier. Thissuggestion is indicated through complementary diachronic searches in the Oxford EnglishDictionary. It is also indicated that the construction may follow a development pattern similarto that of N1 to N1. The notion of construction is discussed in relation to the N1 by N1 construction, and a hierarchical view of constructions is proposed as a solution to some of theproblems with the term.
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Books on the topic "Generic sentence"

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Romanov, Aleksandr. Penal law of the Russian Federation: General and Special parts. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/925785.

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The focus is on the subject and objectives of penal law of the Russian Federation, its sources and methods, types of penal norms, history and types of penal systems, the provisions of the Criminal Executive code of the Russian Federation, other penal laws and normative legal acts on the activities of bodies in charge of execution of punishments, exercising control and supervision over conditionally sentenced persons and persons with a suspended sentence. The characteristic of organization and activity of criminal-Executive system of the Russian Federation, highlights the issues of its reforms. Detail the issues of legal status of convicts established the order and conditions of execution and serving sentences, the use of other measures of criminal-legal nature, means of correction of convicts, providing medical care to prisoners, the performance requirements for the serving of sentences, organisation of support of liberated and control over them. Meets the requirements of Federal state educational standards of higher education of the last generation. For students of law faculties of educational institutions of higher education, enrolled in the academic programs of bachelor, specialist, master and post-graduate students, teachers, practical workers of law enforcement bodies and all those interested in issues of corrections, legal status of prisoners, the penal laws and the application of other measures of criminal-legal nature.
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North Carolina. Administrative Office of the Courts. Presentence reports to judges: Report to the 1988 session of the North Carolina General Assembly. [Raleigh, N.C.] (P.O. Box 2448, Raleigh 27602): The Office, 1988.

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Strzalkowski, Tomek. A meaning representation for generic sentences. New York: Courant Institute of Mathematical Sciences, New York University, 1988.

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Cohen, Ariel. Think generic!: The meaning and use of generic sentences. Stanford, Calif: CSLI, 1999.

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On sentence interpretation. Dordrecht: Kluwer Academic Publishers, 1999.

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Deaf Sentence. London: Penguin, 2009.

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Deaf sentence. New York: Viking, 2008.

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Deaf sentence. London: Harvill Secker, 2008.

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Deaf Sentence. London, UK: Penguin Books Ltd, 2009.

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Lodge, David. Deaf Sentence. New York, NY: Penguin Books, 2008.

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Book chapters on the topic "Generic sentence"

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Lee, Chungmin. "Generic Sentences are Topic Constructions." In Reference and Referent Accessibility, 213. Amsterdam: John Benjamins Publishing Company, 1996. http://dx.doi.org/10.1075/pbns.38.12lee.

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Guéron, Jacqueline. "Generic sentences and bare plurals." In Linguistik Aktuell/Linguistics Today, 219–34. Amsterdam: John Benjamins Publishing Company, 2006. http://dx.doi.org/10.1075/la.95.11gue.

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Rosén, H. "General subordinators and sentence complements." In Studies in Language Companion Series, 197. Amsterdam: John Benjamins Publishing Company, 1989. http://dx.doi.org/10.1075/slcs.17.12ros.

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Panevová, Jarmila. "Sentences with general actor." In Contributions to Functional Syntax, Semantics and Language Comprehension, 203. Amsterdam: John Benjamins Publishing Company, 1985. http://dx.doi.org/10.1075/llsee.16.13pan.

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Mari, Alda. "Another look at Italian generic sentences." In Romance Linguistics 2010, 221–38. Amsterdam: John Benjamins Publishing Company, 2011. http://dx.doi.org/10.1075/cilt.318.14mar.

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Franz d’Avis. "Pejoration, normalcy conceptions and generic sentences." In Linguistik Aktuell/Linguistics Today, 103–18. Amsterdam: John Benjamins Publishing Company, 2016. http://dx.doi.org/10.1075/la.228.05dav.

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Carlson, Greg. "Patterns in the Semantics of Generic Sentences." In Time and Modality, 17–38. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-8354-9_2.

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Carlson, Greg N. "On the Semantic Composition of English Generic Sentences." In Properties, Types and Meaning, 167–92. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2723-0_5.

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Neri-Mendoza, Verónica, Yulia Ledeneva, René Arnulfo García-Hernández, and Ángel Hernández-Castañeda. "Multi-document Text Summarization Based on Genetic Algorithm and the Relevance of Sentence Features." In Lecture Notes in Computer Science, 255–65. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07750-0_24.

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Hart, Steve. "Regions and Countries." In English Exposed. Hong Kong University Press, 2017. http://dx.doi.org/10.5790/hongkong/9789888390755.003.0014.

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This chapter offers instruction on how to refer to countries and regions and how to recognize the differences between the noun and the adjective forms. It also addresses generic and specific sentences, the order of adjectives in a sentence with a country reference, and the capitalization of these terms.
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Conference papers on the topic "Generic sentence"

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Gan, Zhe, Yunchen Pu, Ricardo Henao, Chunyuan Li, Xiaodong He, and Lawrence Carin. "Learning Generic Sentence Representations Using Convolutional Neural Networks." In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/d17-1254.

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Wang, Shaonan, Jiajun Zhang, and Chengqing Zong. "Exploiting Word Internal Structures for Generic Chinese Sentence Representation." In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/d17-1029.

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Krahmer, Emiel, Erwin Marsi, and Paul van Pelt. "Query-based sentence fusion is better defined and leads to more preferred results than generic sentence fusion." In the 46th Annual Meeting of the Association for Computational Linguistics. Morristown, NJ, USA: Association for Computational Linguistics, 2008. http://dx.doi.org/10.3115/1557690.1557745.

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Zha, Hongyuan. "Generic summarization and keyphrase extraction using mutual reinforcement principle and sentence clustering." In the 25th annual international ACM SIGIR conference. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/564376.564398.

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Li, Jing, Aixin Sun, and Shafiq Joty. "SegBot: A Generic Neural Text Segmentation Model with Pointer Network." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/579.

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Text segmentation is a fundamental task in natural language processing that comes in two levels of granularity: (i) segmenting a document into a sequence of topical segments (topic segmentation), and (ii) segmenting a sentence into a sequence of elementary discourse units (EDU segmentation). Traditional solutions to the two tasks heavily rely on carefully designed features. The recently proposed neural models do not need manual feature engineering, but they either suffer from sparse boundary tags or they cannot well handle the issue of variable size output vocabulary. We propose a generic end-to-end segmentation model called SegBot. SegBot uses a bidirectional recurrent neural network to encode input text sequence. The model then uses another recurrent neural network together with a pointer network to select text boundaries in the input sequence. In this way, SegBot does not require hand-crafted features. More importantly, our model inherently handles the issue of variable size output vocabulary and the issue of sparse boundary tags. In our experiments, SegBot outperforms state-of-the-art models on both topic and EDU segmentation tasks.
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Limsopatham, Nut, and Nigel Collier. "Modelling the Combination of Generic and Target Domain Embeddings in a Convolutional Neural Network for Sentence Classification." In Proceedings of the 15th Workshop on Biomedical Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2016. http://dx.doi.org/10.18653/v1/w16-2918.

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Wang, Shaonan, Jiajun Zhang, and Chengqing Zong. "Learning Sentence Representation with Guidance of Human Attention." 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.2017/578.

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Recently, much progress has been made in learning general-purpose sentence representations that can be used across domains. However, most of the existing models typically treat each word in a sentence equally. In contrast, extensive studies have proven that human read sentences efficiently by making a sequence of fixation and saccades. This motivates us to improve sentence representations by assigning different weights to the vectors of the component words, which can be treated as an attention mechanism on single sentences. To that end, we propose two novel attention models, in which the attention weights are derived using significant predictors of human reading time, i.e., Surprisal, POS tags and CCG supertags. The extensive experiments demonstrate that the proposed methods significantly improve upon the state-of-the-art sentence representation models.
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Wei, Liangchen, and Zhi-Hong Deng. "A Variational Autoencoding Approach for Inducing Cross-lingual Word Embeddings." 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.2017/582.

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Cross-language learning allows one to use training data from one language to build models for another language. Many traditional approaches require word-level alignment sentences from parallel corpora, in this paper we define a general bilingual training objective function requiring sentence level parallel corpus only. We propose a variational autoencoding approach for training bilingual word embeddings. The variational model introduces a continuous latent variable to explicitly model the underlying semantics of the parallel sentence pairs and to guide the generation of the sentence pairs. Our model restricts the bilingual word embeddings to represent words in exactly the same continuous vector space. Empirical results on the task of cross lingual document classification has shown that our method is effective.
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Valerie, Shimirwa Aline, and Jian Xu. "Extractive Text Summarization using Recurrent Neural Networks with Attention Mechanism." In 3rd International Conference on Machine Learning & Applications (CMLA 2021). Academy and Industry Research Collaboration Center (AIRCC), 2021. http://dx.doi.org/10.5121/csit.2021.111518.

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Extractive summarization aims to select the most important sentences or words from a document to generate a summary. Traditional summarization approaches have relied extensively on features manually designed by humans. In this paper, based on the recurrent neural network equipped with the attention mechanism, we propose a data-driven technique. We set up a general framework that consists of a hierarchical sentence encoder and an attentionbased sentence extractor. The framework allows us to establish various extractive summarization models and explore them. Comprehensive experiments are conducted on two benchmark datasets, and experimental results show that training extractive models based on Reward Augmented Maximum Likelihood (RAML)can improve the model’s generalization capability. And we realize that complicated components of the state-of-the-art extractive models do not attain good performance over simpler ones. We hope that our work can give more hints for future research on extractive text summarization.
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Anantaram, C., Amit Sangroya, Mrinal Rawat, and Aishwarya Chhabra. "Repairing ASR output by Artificial Development and Ontology based Learning." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/842.

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General purpose automatic speech recognition (gpASR) systems such as Google, Watson, etc. sometimes output inaccurate sentences when used in a domain specific scenario as it may not have had enough training samples for that particular domain and context. Further, the accent of the speaker and the environmental conditions in which the speaker speaks a sentence may influence the speech engine to recognize certain words inaccurately. Many approaches to improve the accuracy of ASR output exist. However, in the context of a domain and the environment in which a speaker speaks the sentences, gpASR output needs a lot of improvement in order to provide effective speech interfaces to domain-specific systems. In this paper, we demonstrate a method that combines bio-inspired artifi- cial development (ArtDev) with machine learning (ML) approaches to repair the output of a gpASR. Our method factors in the environment to tailor the repair process.
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Reports on the topic "Generic sentence"

1

Daume III, Hal, and Daniel Marcu. Generic Sentence Fusion is an Ill-Defined Summarization Task. Fort Belvoir, VA: Defense Technical Information Center, January 2004. http://dx.doi.org/10.21236/ada461416.

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2

Gómez Duque, Lucía del Socorro. Factores que incidieron en la Sentencia C-075-2022 sobre la ley 2075 del 8 de enero del 2021. Contraloría General de Antioquia, January 2023. http://dx.doi.org/10.58373/obscga.005.

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El principal objetivo de la ley 2075 del 8 de enero del 2021 fue: modificar el régimen vigente para la liquidación de honorarios de los concejales de los municipios de cuarta, quinta y sexta categoría, procurando que los valores de los ingresos en ningún momento sean inferiores a un SMMLV (Salario Mínimo Mensual Legal Vigente). Todo aumento por este concepto en comparación con lo que, actualmente, perciban los concejales estará a cargo de la entidad territorial. Las sesiones de comisiones permanentes a las que concurran los concejales se remunerarán por el valor de una reunión ordinaria y tendrán los mismos términos de las sesiones ordinarias. El pago de la cotización al sistema de seguridad social: (pensión, salud, ARL y Cajas de Compensación Familiar) se hará con cargo al presupuesto de la administración municipal. Para financiar los costos de seguridad social de los concejales que reciban ingresos corrientes de libre destinación inferiores a 4.000 SMMLV, se destinará el 0,6% del Sistema General de Participación de Propósito General (tomado del artículo 2 de la ley 1176 de 2007). En este artículo se verificará por medio de un análisis mixto, es decir, cuantitativo y cualitativo, producto del seguimiento normativo aplicable al tema que se va a evaluar.
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