Дисертації з теми "Knowledge and learning in literature"
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1
Franklin, Lee Aaron. "The role of language in Plato's theory of knowledge and learning /." The Ohio State University, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=osu1486398195325073.
Повний текст джерела
2
Ramponi, Alan. "Knowledge Extraction from Biomedical Literature with Symbolic and Deep Transfer Learning Methods." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/310787.
Повний текст джерелаАнотація:
The available body of biomedical literature is increasing at a high pace, exceeding the ability of researchers to promptly leverage this knowledge-rich amount of information. Although the outstanding progress in natural language processing (NLP) we observed in the past few years, current technological advances in the field mainly concern newswire and web texts, and do not directly translate in good performance on highly specialized domains such as biomedicine due to linguistic variations along surface, syntax and semantic levels. Given the advances in NLP and the challenges the biomedical domain exhibits, and the explosive growth of biomedical knowledge being currently published, in this thesis we contribute to the biomedical NLP field by providing efficient means for extracting semantic relational information from biomedical literature texts. To this end, we made the following contributions towards the real-world adoption of knowledge extraction methods to support biomedicine: (i) we propose a symbolic high-precision biomedical relation extraction approach to reduce the time-consuming manual curation efforts of extracted relational evidence (Chapter 3), (ii) we conduct a thorough cross-domain study to quantify the drop in performance of deep learning methods for biomedical edge detection shedding lights on the importance of linguistic varieties in biomedicine (Chapter 4), and (iii) we propose a fast and accurate end-to-end solution for biomedical event extraction, leveraging sequential transfer learning and multi-task learning, making it a viable approach for real-world large-scale scenarios (Chapter 5). We then outline the conclusions by highlighting challenges and providing future research directions in the field.
3
Ramponi, Alan. "Knowledge Extraction from Biomedical Literature with Symbolic and Deep Transfer Learning Methods." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/310787.
Повний текст джерелаАнотація:
The available body of biomedical literature is increasing at a high pace, exceeding the ability of researchers to promptly leverage this knowledge-rich amount of information. Although the outstanding progress in natural language processing (NLP) we observed in the past few years, current technological advances in the field mainly concern newswire and web texts, and do not directly translate in good performance on highly specialized domains such as biomedicine due to linguistic variations along surface, syntax and semantic levels. Given the advances in NLP and the challenges the biomedical domain exhibits, and the explosive growth of biomedical knowledge being currently published, in this thesis we contribute to the biomedical NLP field by providing efficient means for extracting semantic relational information from biomedical literature texts. To this end, we made the following contributions towards the real-world adoption of knowledge extraction methods to support biomedicine: (i) we propose a symbolic high-precision biomedical relation extraction approach to reduce the time-consuming manual curation efforts of extracted relational evidence (Chapter 3), (ii) we conduct a thorough cross-domain study to quantify the drop in performance of deep learning methods for biomedical edge detection shedding lights on the importance of linguistic varieties in biomedicine (Chapter 4), and (iii) we propose a fast and accurate end-to-end solution for biomedical event extraction, leveraging sequential transfer learning and multi-task learning, making it a viable approach for real-world large-scale scenarios (Chapter 5). We then outline the conclusions by highlighting challenges and providing future research directions in the field.
4
Radovanovic, Aleksandar. "Concept Based Knowledge Discovery from Biomedical Literature." Thesis, Online access, 2009. http://etd.uwc.ac.za/usrfiles/modules/etd/docs/etd_gen8Srv25Nme4_9861_1272229462.pdf.
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5
Clavijo-Olarte, Amparo. "Knowledge of literacy learning by Colombian teachers of Spanish and of English." Diss., The University of Arizona, 1999. http://hdl.handle.net/10150/284080.
Повний текст джерелаАнотація:
The purpose of this research study is to analyze Colombian teachers' knowledge of literacy learning in Spanish and in English revealed in their narratives and in their practice through a teacher education program. The research questions addressed in this study aim to answer the following: (1) How do teachers in the literacy program perceive reading and writing as revealed through their personal literacy histories? (2) What knowledge of literacy learning in Spanish and in English do teachers in the literacy program reveal as presented in their self-selected classroom literacy project? (3) How is teachers' knowledge of literacy learning in Spanish and in English expressed in their practice? This study draws upon data collected during a year-long inquiry I conducted with public school teachers in Bogota, Colombia during March 1998 and April 1999. The 42 teachers who participated in this research project had an average of 10 years teaching. Their knowledge statements found in the data collected served as the unit of analysis from which six categories emerged. Additional information represented in classroom observation, interviews and videotapes was collected of three exemplar cases of elementary school teachers. The conclusions that I arrived at from the analysis of Colombian teachers' knowledge of literacy learning are the following: First, that writing and sharing the literacy histories contributed to transforming traditional pedagogical practices into innovative pedagogical practices of reading and writing. Second, the class sessions, readings, seminars attended, and the sharing of experiences with their peers permitted the generation of new knowledge on literacy learning by teachers. Third, the new knowledge of literacy learning generated by teachers was revealed in the innovations presented in their classroom literacy project. Finally, the conference on literacy contributed to exchanging knowledge and generating more questions for further investigation.
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Beierle, Marlene Perlman. "Classroom Interactions that Support Learning Over time: The Construction of Learning Opportunities for Acquiring Complex Academic Knowledge in the Study of Literature." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1324177693.
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Da, Silva Maia Alexandre. "Renaissance desire and disobedience : eroticizing human curiosity and learning in Doctor Faustus." Thesis, McGill University, 1998. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=21205.
Повний текст джерелаАнотація:
Focusing on the A-text (1604) version of Marlowe's Doctor Faustus , this study further assesses biographical information on the poet and intellectual currents of the Counter Reformation, so as to investigate the play's relation to emergent trends of individualism in the Renaissance, recovery of the pagan past, and intellectual aspirations that could readily collide with orthodoxy. Clearly reflecting anxieties of the period about individual deviance from social norms through intellectual overreaching, Doctor Faustus powerfully testifies to the potential dangers of human aspiration and the scholarly spirit of unbounded learning. While thus exploring the exotic temptations of forbidden knowledge, the play resurrects and interrogates traditional taboos which related intellectual appetite to wrongful lust. Marlowe stages an explosive conflict between the conservative tradition of intellectual inquiry, which distrusted the unorthodox scholarship and Neoplatonic magic that some widely influential thinkers promoted in the Italian Renaissance, and Faustus's own creative desires, ambitions, and imagination. The tension between proscribed and prescribed knowledge climaxes in the invocation of Helen of Troy. While Helen's significance is complex, we find that, in relation to the play's concern with dissent from orthodoxy, she focuses the power of intellectual longing to seduce and ravish the mind. Apart from being a superior play, Doctor Faustus encapsulates Marlowe's awareness of his period's uneasy perception of unconventional thinking, and urges the importance of challenging restrictions on how much one is permitted to know.
8
Sjödin, Emma. ""One goal is to understand the world better" : A Thematic Analysis of Upper-Secondary School Teachers' Choice and Use of Literary Texts in EFL." Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-47932.
Повний текст джерелаАнотація:
The aims of the present study were to explore how teachers in upper-secondary school choose and use literary texts and genres in their teaching of English as a foreign language (EFL), what their attitudes are towards the role of literature in reaching the learning objectives and what implications their textual choices have for literature teaching in general. Six people participated in the study, three male and three female upper-secondary school teachers in Sweden with English as one of their main subjects. The data were collected through semi-structured interviews with questions focusing on how the teachers use literary texts in order to teach English in the courses English 5, 6 and 7. The data were analysed using a grounded theory approach. The identified themes were teachers’ general attitudes to literature teaching, learning objectives taught implicitly through literature and teachers’ basis for literary choices. The main conclusions drawn from this study were that in most of these cases, factors such as relatability and degree of intelligible input overrode canonicity in EFL literature teaching.
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Johannesson, Emelie. "Video games – A tool for expanding English vocabulary knowledge? : A study of video games potential impact on English vocabulary knowledge in Swedish upper secondary students." Thesis, Karlstads universitet, Institutionen för språk, litteratur och interkultur (from 2013), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-78802.
Повний текст джерелаАнотація:
This study researches the possibility of video games being a helpful tool when it comes to English vocabulary knowledge, by comparing the English vocabulary knowledge of those that play video games to those that do not play video games. The study also focuses on comparing the English vocabulary knowledge of those that play video games frequently to those that play video games seldomly and discuss why this might make a difference. 37 students were asked to fill in a questionnaire with questions focusing on if they play video games or not, how often they play and what sort of games they played. The second part of the study was a vocabulary test containing 51 words one might encounter whilst playing video games, in this vocabulary test the students were asked to give an English synonym and a Swedish translation of these words. The results of the study revealed that there were differences between the groups, as those that did play video games scored higher on the vocabulary test compared to those that did not play video games. There was also a difference in terms of performance on the vocabulary test depending on how often the students played video games.Denna studie undersöker videospels möjlighet till att vara ett hjälpmedel när det gäller kunskaper i engelskt ordförråd genom att jämföra ordförrådskunskaperna hos de som spelar videospel med de som inte spelar videospel. Studien fokuserar också på att jämföra de engelska ordförrådskunskaperna hos dem som ofta spelar videospel med de som sällan spelar videospel och diskuterar varför detta kan göra en skillnad. 37 elever ombads att fylla i ett frågeformulär med frågor med fokus på om de spelar videospel eller inte, hur ofta de spelar och vilken typ av spel de spelade. Den andra delen av studien var ett ordförrådstest innehållande 51 ord som kan stötas på i videospel, i detta ordförrådstest ombads eleverna att ge en engelsk synonym och en svensk översättning av dessa ord. Resultaten av studien visade att det fanns skillnader mellan grupperna, eftersom de som spelade videospel fick högre poäng på ordförrådstestet jämfört med de som inte spelade videospel. Det fanns också skillnader prestationsmässigt i ordförrådstestet beroende på hur ofta eleverna spelade videospel.
10
Tivehag, Evelina. "Det främmande ordet : Att arbeta med ordinlärning i det engelska språket i grundskolan." Thesis, Karlstads universitet, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-80076.
Повний текст джерелаАнотація:
Detta arbete hade syftet att undersöka hur det arbetas med ordinlärning i engelskundervisningen i den svenska grundskolan. Studien är baserad på intervjuer med syfte att undersöka lärares syn på ordinlärning och vilka metoder de finner mest gynnande för den långsiktiga inlärningen. Intervjuerna var semistrukturerade och genomfördes med hjälp av två lärare som undervisar i årskurserna 1-3 och tre lärare som undervisar i årskurserna 4-6. Resultaten visar att det finns olika metoder som används vid ordinlärning och dessa inkluderar att läraren genemsamt läser och uttalar ord tillsammans med sina elever, samt att uppmärksamma nya ord i texter under läsningens gång. Lärarnas svar visade även att lärarna medvetet integrerar olika metoder i undervisningen för att gynna elevernas ordinlärning. Lärarna säger att de märker vilka metoder eleverna föredrar, vilket bland annat involverar samarbeten, webbaserade aktiviteter och läsning i grupp. Lärarna säger även att det genom undervisningen framgår vilka metoder som är mest gynnsamma än andra.
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Lankford, Angela Celestine. "Learning to "Teacher Think": Using English Education as a Model for Writing Teacher Preparation in the Composition Practicum." BYU ScholarsArchive, 2013. https://scholarsarchive.byu.edu/etd/3849.
Повний текст джерелаАнотація:
This study explores the impact of "teacher thinking" exercises in the Composition Practicum as a means of instilling a clearer sense of professional development in graduate instructors. Teacher thinking is a teacher training method that asks the novice instructor to see from the perspective of learners within their writing classrooms. Scholarship on writing teacher preparation programs suggests that English educators regularly employ teacher thinking exercises in the training of secondary school teachers. Teacher thinking has allowed many English education majors to conceptualize and obtain teaching identities by helping them to envision the intricate layers of teaching earlier in their careers. But can teacher thinking exercises have the same effect on graduate instructors in the Composition Practicum? Using the two main writing teacher preparation courses at Brigham Young University (BYU) for graduate instructors and English education majors, English 610 and English 423, I analyze the evidence of teacher thinking in each program and address the possible implications these findings could hold for the Composition Practicum course. Through my comparison of these courses, I determine if conversations between English educators and the Composition Practicum could be beneficial in helping graduate instructors to grow professionally as teachers as they learn to think like teachers in the Composition Practicum. I examine, analyze, and compare syllabi, surveys, and interview response from graduate instructors, English education majors, and the teachers of both courses to identify the types of teaching thinking students are exposed to in each course. Structuring my discussion around the teacher thinking theories of teacher educators, Forrest Parkay and Beverly Stanford, George Hillocks, and Alicia Crowe and Amanda Berry, I identify three types of knowledge that graduate instructors and English education majors gained or lacked in each program. These three types of knowledge are knowledge of self, knowledge of students, and knowledge of educational theory. Through this discussion, I explore what it means to think like a composition teacher and how learning to "teacher think" may help graduate instructors, nationally, to understand what it means to "simply be a composition teacher".
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Turesson, Jesper. "Kunskapssynen i teknikämnetskursplan." Thesis, KTH, Lärande, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-213752.
Повний текст джерелаАнотація:
Grundskolans teknikämne har kritiserats för att undervisningen inte utgår från elevernas intressen och erfarenheter. Vidare utgår undervisningen alltför sällan från kursplanen och det saknas en samsyn bland lärarna kring hur undervisningen skall genomföras samt vad ämnet står för. Beträffande det sistnämnda har studier visat att filosofiska diskussioner om hur teknik kan definieras inte är vanliga inom teknikdidaktiken, vilket kan få konsekvenser när gemensamma kriterier ska sättas upp för att användas vid bedömning och betygsättning av elevernas kunskaper. Detta examensarbete har som syfte att undersöka hur teknik och teknisk kunskap kan definieras och på vilket sätt dessa begrepp förekommer i de styrdokument som skolorna har att förhålla sig till. Det är en systematisk litteraturstudie där den tidigare forskningen i ämnet har undersökts och där teknikämnets kursplan har analyserats utifrån denna forskning. Resultatet visar att även om det i skolans läroplan saknas filosofiska diskussioner om vad teknisk kunskap innebär, går det att finna spår av denna typ av kunskap. Exempelvis kännetecknas teknikämnet av de teknikutvecklingsprojekt som eleverna skall genomföra och i dessa projekt får de möjlighet att utveckla så kallade teknikvetenskapliga kunskaper genom att de systematiskt prövar och omprövar sina idéer.The technology subject in Swedish elementary school has been criticised for not taking into account the pupils interests and experiences. Furthermore, the teaching is often not based on the curriculum and there is a lack of consensus among the teacher on what should be taught and what the subject stands for. Regarding the latter, studies have shown that philosophical discussions on the definition of technology are not common within technology teaching and learning, which can have consequences when a common set of criteria are set up to be used for assessment and grade setting. This study examines how technology and technological knowledge can be defined and how these concepts are reflected in the curriculum. Based on a systematic literature review of former studies in this area, an analysis of the curriculum is performed. The result show that even if there is a lack of philosophical discussions in the curriculum on what technological knowledge means, traces of this type of knowledge can be found. As an example the technology subject is characterised by the technical development projects that the pupils are supposed to carry out, and in these projects they get the opportunity to develop the so called technological science knowledge by systematically testing and re-testing their ideas.
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Souza, Ana Paula Gestoso de. "Histórias infantis e matemática : a mobilização de recursos, a apropriação de conhecimentos e a receptividade de alunos de 4ª série do ensino fundamental." Universidade Federal de São Carlos, 2008. https://repositorio.ufscar.br/handle/ufscar/2454.
Повний текст джерелаАнотація:
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Previous issue date: 2008-07-28Considering a teaching/learning environment where literature and mathematics were connected, this research tried to investigate the ways by which the students of a fourth grade elementary school class acquired the school content, managed it and accepted the proposed methodology. In the theoretical reference, we discuss concepts and ideas such as: the perspectives of some authors on knowledge fragmentation and how it takes place in school; the means by which knowledge can be addressed in school; and the relationship of the students with such knowledge and with the teaching/learning context in which they are placed. We also discuss the impregnation of language with mathematics, the potential of reading, and the possibilities of developing a methodology that connects education, language, literature and mathematics. This research was developed in a fourth grade class of a public school in São Carlos (São Paulo State) according to a pedagogical sequence that articulated mathematics and children s literature the books chosen were The duck s lollipop and Sweet Fractions . The mathematical content developed was: fraction concept of part-whole, comparison and equivalence of fractions. The classes were recorded on video. Other information includes the number of students 33 and the fact that all of them participated in the pedagogical intervention, although only 13 had their learning processes and exercises analysed: the ones who had authorized us to do so. During the development of the pedagogical intervention, we could notice that many students were receptive to the work proposed i.e., the connection between literature and mathematics and acted as active subjects, taking part in the activities. Another aspect to point out is the importance of the use of manipulative materials for the students learning, because they allowed the children to come up with their own thoughts, and to produce and test hypotheses and strategies, getting involved in the process of understanding the material presented. By investigating the learning process of these students, we emphasize the educator s role as a mediator who, being aware of the previous knowledge of the students about certain subjects and understanding the strategies used by them to solve a situation, will be able to use some conditions and effective interventions in order to enable the students reasoning. Therefore, the students developed assumptions, strategies and interacted with the narratives, constructed mathematical notions, established a relationship of interiority with the knowledge, and the process itself involved the personal knowledge, life stories and experiences, i.e, the uniquenesses of each human subject who is part of the educational process and who creates himself/herself in daily school life, also creating the whole environment.
Esta pesquisa buscou investigar de que maneiras os alunos da 4ª série do Ensino Fundamental, em um contexto de ensino e aprendizagem que conectou literatura e matemática, se apropriaram dos conteúdos escolares, se relacionaram com esses conhecimentos e qual foi a receptividade deles a essa metodologia. O referencial teórico discute conceitos e idéias como: as perspectivas de alguns autores sobre a fragmentação do conhecimento e como essa fragmentação ocorre na escola, as formas como o conhecimento pode ser abordado no âmbito escolar (forma de conhecimento tópico, como operação e situacional) e as relações que os alunos estabelecem com esse conhecimento e com as situações de ensino e aprendizagem nas quais se inserem. Esse referencial também discute a impregnação mútua existente entre língua materna e matemática, as potencialidades da leitura, bem como as possibilidades de desenvolver uma metodologia de ensino que articule língua materna, literatura e matemática. Nesse cenário, desenvolvemos uma seqüência didática em uma sala de 4ª série em uma escola da rede estadual de São Carlos, SP, que articulou matemática e literatura infantil a partir dos livros O pirulito do Pato e Doces Frações , sendo que os conteúdos matemáticos abordados foram: a noção de fração enquanto subconstruto parte-todo, comparação e equivalência de frações. Destaco também que as aulas ministradas foram gravadas em vídeo. Além disso, assinalo que essa classe era composta por 33 alunos e todos participaram da intervenção didática, mas analisamos apenas as produções e processos de aprendizagem de 13 crianças que nos autorizaram a isso. Durante o desenvolvimento da seqüência didática, constatamos que vários alunos foram receptivos ao trabalho proposto a articulação entre literatura e matemática e agiram como sujeitos ativos, colocando-se em atividade frente a essa metodologia. Também é possível assinalar a importância do uso de materiais manipuláveis para a aprendizagem dos alunos, pois, a partir desse tipo de material, os participantes da pesquisa elaboraram seus pensamentos, criaram e testaram hipóteses e estratégias, envolvendo-se num processo de compreensão dos conteúdos abordados. Investigando o processo de aprendizagem desses alunos, enfatizamos o papel do professor como um mediador, que, ao ter ciência dos conhecimentos prévios dos alunos acerca de determinado conteúdo e compreendendo as estratégias usadas por eles para resolver uma situação, poderá dispor de condições e efetivar intervenções necessárias a fim de possibilitar o raciocínio dos alunos. Enfim, constatamos que os estudantes elaboraram hipóteses, estratégias e interagiram com as narrativas, construindo conhecimento e estabelecendo uma relação de interioridade com os saberes abordados nas aulas, sendo que esse processo envolveu os saberes próprios, as histórias e experiências de vida, ou seja, as singularidades de cada sujeito que faz parte do processo educativo, que se constitui no cotidiano escolar e que forma esse ambiente.
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Salii, Helena. "Teaching Kazuo Ishiguro’s The Remains of the Day : A Theoretical Essay Towards Cross-Curricular, DualCoded Historical Knowledge." Thesis, Högskolan i Halmstad, Akademin för lärande, humaniora och samhälle, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-40764.
Повний текст джерелаАнотація:
In a suggestion to build upon students’ historical knowledge through reading The Remains of the Day, this essay delves into cross-curricular teaching, dual-coded theory aspects and revision of suggested plans to improve learner’s understanding of historical novels, characters, events, and descriptions to grasp and reflect upon such historical knowledge. Several methods for enhancing students’ knowledge and to improve vocabulary knowledge are provided. The essay is theoretically based and presents different aspects of how students’ knowledge of English and history as separate subjects in school, could be combined to address the learning abilities of all students. Reading comprehension is mainly based upon students’ prior knowledge. Therefore, this essay delves into various parts of learners’ abilities to reflect upon the written word and its significance to reality. Furthermore, suggestions to how teachers can collaborate to achieve an improved understanding of the novel and its time period through history and vocabulary is presented.
15
Kiehl, Janet K. "Learning to Change: Organizational Learning and Knowledge Transfer." online version, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=case1080608710.
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Chan, Ngai-man, and 陳艾敏. "An examination of the interplay of knowledge types, knowledge workers and knowledge creation in knowledge management." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B31245158.
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陳淑霞 and Shuk-ha Louisa Chan. "Student motivation in knowledge forum on fostering knowledge building communities." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B31256594.
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Ghiasnezhad, Omran Pouya. "Rule Learning in Knowledge Graphs." Thesis, Griffith University, 2018. http://hdl.handle.net/10072/382680.
Повний текст джерелаАнотація:
With recent advancements in knowledge extraction and knowledge management
systems, an enormous number of knowledge bases have been constructed, such as
YAGO, and Wikidata. These automatically built knowledge bases which contain
millions of entities and their relations have been stored in graph-based schemas,
and thus are usually referred to as knowledge graphs (KGs).
Since KGs have been built based on the limited available data, they are far from
complete. However, learning frequent patterns in the form of logical rules from
these incomplete KGs has two main advantages. First, by applying the learned
rules, we can infer new facts, so we could complete the KGs. Second, the rules are
stand-alone knowledge which express valuable insight about the data.
However, learning rules from KGs in relation to the real-world scenarios imposes
several challenges. First, due to the vast size of real-world KGs, developing a
rule learning method is challenging. In fact, existing methods are not scalable for
learning rst order rules, while various optimisation strategies are used such as
sampling and language bias (i.e., restrictions on the form of rules). Second, applying
the learned rules to the vast KG and inferring new facts is another di cult
issue. Learned rules usually contain a lot of noises and adding new facts can cause
inconsistency of KGs. Third, it is useful but non-trivial to extend an existing
method of rule learning to the case of stream KGs. Forth, in many data repositories,
the facts are augmented with time stamps. In this case, we face a stream of
data (KGs). Considering time as a new dimension of data imposes some challenges
to the rule learning process. It would be useful to construct a time-sensitive model
from the stream of data and apply the obtained model to stream KGs. Last, the
density of information in a KG is varied. Although the size of a KG is vast, it
contains a limited amount of information for some relations. Consequently, that
part of KG is sparse. Learning a set of accurate and informative rules regarding
the sparse part of a KG is challenging due to the lack of su cient training data.
In this thesis, we investigate these research problems and present our methods for
rule learning in various scenarios. We have rst developed a new approach, named Rule Learning via Learning Representation (RLvLR), to learning rules from KGs
by using the technique of embedding in representation learning together with a
new sampling method. RLvLR learns rst-order rules from vast KGs by exploring
the embedding space. It can handle some large KGs that cannot be handled by
existing rule learners e ciently, due to a novel sampling method. To improve the
performance of RLvLR for handling sparse data, we propose a transfer learning
method, Transfer Rule Learner (TRL), for rule learning. Based on a similarity
characterised by the embedding representation, our method is able to select most
relevant KGs and rules to transfer from a pool of KGs whose rules have been
obtained. We have also adapted RLvLR to handle stream KGs instead of static
KGs. Then a system called StreamLearner is developed for learning rules from
stream KGs. These proposed methods can only learn so-called closed path rules,
which is a proper subset of Horn rules. Thus, we have also developed a transfer
rule learner (T-LPAD) that learns the structure of logic program with annotated
disjunctions. T-LPAD is created by employing transfer learning to explore the
space of rules' structures more e ciently.
Various experiments have been conducted to test and validate the proposed methods.
Our experimental results show that our methods outperform state-of-the-art
methods in many ways.Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Info & Comm Tech
Science, Environment, Engineering and Technology
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Zhang, Ping. "Learning from Multiple Knowledge Sources." Diss., Temple University Libraries, 2013. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/214795.
Повний текст джерелаАнотація:
Computer and Information SciencePh.D.
In supervised learning, it is usually assumed that true labels are readily available from a single annotator or source. However, recent advances in corroborative technology have given rise to situations where the true label of the target is unknown. In such problems, multiple sources or annotators are often available that provide noisy labels of the targets. In these multi-annotator problems, building a classifier in the traditional single-annotator manner, without regard for the annotator properties may not be effective in general. In recent years, how to make the best use of the labeling information provided by multiple annotators to approximate the hidden true concept has drawn the attention of researchers in machine learning and data mining. In our previous work, a probabilistic method (i.e., MAP-ML algorithm) of iteratively evaluating the different annotators and giving an estimate of the hidden true labels is developed. However, the method assumes the error rate of each annotator is consistent across all the input data. This is an impractical assumption in many cases since annotator knowledge can fluctuate considerably depending on the groups of input instances. In this dissertation, one of our proposed methods, GMM-MAPML algorithm, follows MAP-ML but relaxes the data-independent assumption, i.e., we assume an annotator may not be consistently accurate across the entire feature space. GMM-MAPML uses a Gaussian mixture model (GMM) and Bayesian information criterion (BIC) to find the fittest model to approximate the distribution of the instances. Then the maximum a posterior (MAP) estimation of the hidden true labels and the maximum-likelihood (ML) estimation of quality of multiple annotators at each Gaussian component are provided alternately. Recent studies show that it is not the case that employing more annotators regardless of their expertise will result in improved highest aggregating performance. In this dissertation, we also propose a novel algorithm to integrate multiple annotators by Aggregating Experts and Filtering Novices, which we call AEFN. AEFN iteratively evaluates annotators, filters the low-quality annotators, and re-estimates the labels based only on information obtained from the good annotators. The noisy annotations we integrate are from any combination of human and previously existing machine-based classifiers, and thus AEFN can be applied to many real-world problems. Emotional speech classification, CASP9 protein disorder prediction, and biomedical text annotation experiments show a significant performance improvement of the proposed methods (i.e., GMM-MAPML and AEFN) as compared to the majority voting baseline and the previous data-independent MAP-ML method. Recent experiments include predicting novel drug indications (i.e., drug repositioning) for both approved drugs and new molecules by integrating multiple chemical, biological or phenotypic data sources.
Temple University--Theses
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Desimone, Roberto V. "Learning control knowledge within an explanation-based learning framework." Thesis, University of Edinburgh, 1989. http://hdl.handle.net/1842/18827.
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Van, Aalst Jan C. W. "Learning, knowledge building, and subject matter knowledge in school science." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0003/NQ41331.pdf.
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Efthymiadis, Kyriakos. "Knowledge-based reward shaping with knowledge revision in reinforcement learning." Thesis, University of York, 2014. http://etheses.whiterose.ac.uk/9166/.
Повний текст джерелаАнотація:
Reinforcement learning has proven to be a successful artificial intelligence technique when an agent needs to act and improve in a given environment. The agent receives feedback about its behaviour in terms of rewards through constant interaction with the environment and in time manages to identify which actions are more beneficial for each situation. Typically reinforcement learning assumes the agent has no prior knowledge about the environment it is acting on. Nevertheless, in many cases (potentially abstract and heuristic) domain knowledge of the reinforcement learning tasks is available by domain experts, and can be used toimprove the learning performance. One way of imparting knowledge to an agent is through reward shaping which guides an agent by providing additional rewards. One common assumption when imparting knowledge to an agent, is that the domain knowledge is always correct. Given that the provided knowledge is of a heuristic nature, there are cases when this assumption is not met and it has been shown that in cases where the provided knowledge is wrong, the agent takes longer to learn the optimal policy. As reinforcement learning methods are shifting more towards informed agents, the assumption that expert domain knowledge is always correct needs to be relaxed in order to scale these methods to more complex, real-life scenarios. To accomplish that, the agents need to have a mechanism to deal with those cases where the provided expert knowledge is not perfect. This thesis investigates and documents the adverse effects erroneous knowledge can have to the learning process of an agent if care is not taken. Moreover, it provides a novel approach to deal with erroneous knowledge through the use of knowledge revision principles, in order to allow agents to use their experiences to revise knowledge and thus benefit from more accurate shaping. Empirical evaluation shows that agents that are able to revise erroneous parts of the provided knowledge, can reach better policies faster when compared to agents that do not have knowledge revision capabilities.
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Kabel, Suzanna Catharina. "Knowledge-rich indexing of learning objects." [S.l. : Amsterdam : s.n.] ; Universiteit van Amsterdam [Host], 2004. http://dare.uva.nl/document/74617.
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Pilkington, R. "Knowledge-based systems in topic learning." Thesis, University of Leeds, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.380324.
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Yang, Charles D. "Knowledge and learning in natural language." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86586.
Повний текст джерелаАнотація:
Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2001.Includes bibliographical references (p. 128-140).
by Charles D. Yang.
Ph.D.
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Atkeson, Christopher Granger. "Roles of knowledge in motor learning." Thesis, Massachusetts Institute of Technology, 1986. http://hdl.handle.net/1721.1/29195.
Повний текст джерелаАнотація:
Thesis (Ph. D.)--Massachusetts Institute of Technology, Whitaker College of Health Sciences, Technology, and Management, Dept. of Brain and Cognitive Sciences, 1986.MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE
Bibliography: leaves 143-154.
by Christopher Granger Atkeson.
Ph.D.
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Forbes, Charles L. (Charles Lockwood). "Organizational learning--from information to knowledge." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/10605.
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Aljohani, Eman Marzouq. "Learning graphical models using prior knowledge." Thesis, University of York, 2015. http://etheses.whiterose.ac.uk/10045/.
Повний текст джерелаАнотація:
Graphical models represent conditional independence relationships between variables, including, for example, those between the various symptoms and causes of a disease. An important topic in the area of machine learning is learning these types of models from data. In some applications, it is crucial to include information that is not contained in the data, i.e. prior information. The aim of this research is to design an efficient algorithm that utilises prior knowledge in a manner which allows users to express what they know about the problem domain. This involves creating a system where the input is composed of prior knowledge, together with data, connected to a Bayesian learning algorithm. Our main aim is to facilitate the design of an algorithm that uses prior knowledge ahead of time, in order to both speed up the process of learning and ensure that the learning is more accurate.
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Sykes, Chris. "Efficient management, wasted knowledge? : a critical investigation of organisational knowledge in community services organisations." Thesis, Faculty of Business and Economics, 2007. http://hdl.handle.net/2123/12309.
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Aamot, Elias. "Literature-based knowledge discovery in climate science." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-27047.
Повний текст джерелаАнотація:
Climate change caused by anthropogenic activity is one of the biggest challenges of our time. Researchers are striving to understand the effects of global warming on the ecological systems of the oceans, and how these ecological systems influence the global climate, a line of research that is crucial in order to counteract or adapt to the effects of global warming. A major challenge that researchers in this area are facing, is the huge amount of potentially relevant literature, as insights from widely different fields such as biology, chemistry, climatology and oceanography can prove crucial in understanding the effects of global warming on the oceans. To alleviate some of the work load from researchers, information extraction tools can be used to extract relevant information from the scientific literature automatically, and discovery support tools can be developed to assist researchers in their efforts. This master thesis conducts fundamental research into the development of discovery support tools for oceanographic climate science, focusing primarily on the information extraction component.
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Jha, Kishlay. "Mining Novel Knowledge from Biomedical Literature using Statistical Measures and Domain Knowledge." Thesis, North Dakota State University, 2016. https://hdl.handle.net/10365/28085.
Повний текст джерелаАнотація:
The problem of inferring novel knowledge from implicit facts by logically connecting independent fragments of literature is known as Literature Based Discovery (LBD). In LBD, to discover hidden links, it is important to determine the relevancy between concepts using appropriate information measures. In this study, to discover interesting and inherent links latent in large corpora, nine distinct methods, comprising variants of statistical information measures and derived semantic knowledge from domain ontology, are designed and compared. A series of experiments are performed and analyzed for those proposed methods. Also, a new strategy of effective preprocessing is proposed, which is capable of removing terms that have meager chances of constituting a new discovery. Finally, an organized list of final concepts deemed worthy of scientific investigation are provided to the user. Overall, our research presents a comprehensive analysis and perspective of how different statistical information measures and semantic knowledge affect the knowledge discovery procedure.
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Bernacki, Matthew L. "The influence of self-regulated learning and prior knowledge on knowledge acquisition in computer-based learning environments." Diss., Temple University Libraries, 2010. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/78622.
Повний текст джерелаАнотація:
Educational PsychologyPh.D.
This study examined how learners construct textbase and situation model knowledge in hypertext computer-based learning environments (CBLEs) and documented the influence of specific self-regulated learning (SRL) tactics, prior knowledge, and characteristics of the learner on posttest knowledge scores from exposure to a hypertext. A sample of 160 undergraduate education majors completed measures of prior knowledge, goal orientation, intrinsic motivation, self-efficacy to self-regulate learning, and a demographic survey. They were trained in the use of nStudy, a learning environment designed to facilitate self-regulated learning from web-based media including hypertext and to trace learners' actions while they learned online. Learners completed a 20-minute study session learning about Attention Deficit Hyperactivity Disorder and a posttest to assess changes in knowledge scores. Results indicate that employment of individual SRL tactics including tendency to highlight was found to be associated with increased posttest knowledge scores across learners. Goal orientation and prior knowledge also significantly predicted posttest knowledge scores in regression models. These findings can be used to inform the design and use of hypertext in order to individualize computer-based instruction and maximize knowledge acquisition for students, based upon their individual characteristics.
Temple University--Theses
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Choi, Jin-Woo. "Action Recognition with Knowledge Transfer." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/101780.
Повний текст джерелаАнотація:
Recent progress on deep neural networks has shown remarkable action recognition performance from videos. The remarkable performance is often achieved by transfer learning: training a model on a large-scale labeled dataset (source) and then fine-tuning the model on the small-scale labeled datasets (targets). However, existing action recognition models do not always generalize well on new tasks or datasets because of the following two reasons. i) Current action recognition datasets have a spurious correlation between action types and background scene types. The models trained on these datasets are biased towards the scene instead of focusing on the actual action. This scene bias leads to poor generalization performance. ii) Directly testing the model trained on the source data on the target data leads to poor performance as the source, and target distributions are different. Fine-tuning the model on the target data can mitigate this issue. However, manual labeling small- scale target videos is labor-intensive. In this dissertation, I propose solutions to these two problems. For the first problem, I propose to learn scene-invariant action representations to mitigate the scene bias in action recognition models. Specifically, I augment the standard cross-entropy loss for action classification with 1) an adversarial loss for the scene types and 2) a human mask confusion loss for videos where the human actors are invisible. These two losses encourage learning representations unsuitable for predicting 1) the correct scene types and 2) the correct action types when there is no evidence. I validate the efficacy of the proposed method by transfer learning experiments. I trans- fer the pre-trained model to three different tasks, including action classification, temporal action localization, and spatio-temporal action detection. The results show consistent improvement over the baselines for every task and dataset. I formulate human action recognition as an unsupervised
domain adaptation (UDA) problem to handle the second problem. In the UDA setting, we have many labeled videos as source data and unlabeled videos as target data. We can use already exist- ing labeled video datasets as source data in this setting. The task is to align the source and target feature distributions so that the learned model can generalize well on the target data. I propose 1) aligning the more important temporal part of each video and 2) encouraging the model to focus on action, not the background scene, to learn domain-invariant action representations. The proposed method is simple and intuitive while achieving state-of-the-art performance without training on a lot of labeled target videos. I relax the unsupervised target data setting to a sparsely labeled target data setting. Then I explore the semi-supervised video action recognition, where we have a lot of labeled videos as source data and sparsely labeled videos as target data. The semi-supervised setting is practical as sometimes we can afford a little bit of cost for labeling target data. I propose multiple video data augmentation methods to inject photometric, geometric, temporal, and scene invariances to the action recognition model in this setting. The resulting method shows favorable performance on the public benchmarks.Doctor of Philosophy
Recent progress on deep learning has shown remarkable action recognition performance. The remarkable performance is often achieved by transferring the knowledge learned from existing large-scale data to the small-scale data specific to applications. However, existing action recog- nition models do not always work well on new tasks and datasets because of the following two problems. i) Current action recognition datasets have a spurious correlation between action types and background scene types. The models trained on these datasets are biased towards the scene instead of focusing on the actual action. This scene bias leads to poor performance on the new datasets and tasks. ii) Directly testing the model trained on the source data on the target data leads to poor performance as the source, and target distributions are different. Fine-tuning the model on the target data can mitigate this issue. However, manual labeling small-scale target videos is labor-intensive. In this dissertation, I propose solutions to these two problems. To tackle the first problem, I propose to learn scene-invariant action representations to mitigate background scene- biased human action recognition models for the first problem. Specifically, the proposed method learns representations that cannot predict the scene types and the correct actions when there is no evidence. I validate the proposed method's effectiveness by transferring the pre-trained model to multiple action understanding tasks. The results show consistent improvement over the baselines for every task and dataset. To handle the second problem, I formulate human action recognition as an unsupervised learning problem on the target data. In this setting, we have many labeled videos as source data and unlabeled videos as target data. We can use already existing labeled video datasets as source data in this setting. The task is to align the source and target feature distributions so that the learned model can generalize well on the target data. I propose 1) aligning the more important temporal part of each video and 2) encouraging the model to focus on action, not the background scene. The proposed method is simple and intuitive while achieving state-of-the-art performance without training on a lot of labeled target videos. I relax the unsupervised target data setting to a sparsely labeled target data setting. Here, we have many labeled videos as source data and sparsely labeled videos as target data. The setting is practical as sometimes we can afford a little bit of cost for labeling target data. I propose multiple video data augmentation methods to inject color, spatial, temporal, and scene invariances to the action recognition model in this setting. The resulting method shows favorable performance on the public benchmarks.
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Desbrisay, Cecelia Gay Miller. "Giambattista Vico : imagination and historical knowledge." Thesis, University of Oxford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359696.
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Klassen, Norman John. "Chaucer on love, knowledge, and sight." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.356989.
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Thaul, Witold. "Supporting learning by tracing personal knowledge formation." Thesis, University of Plymouth, 2014. http://hdl.handle.net/10026.1/3030.
Повний текст джерелаАнотація:
Internet-based and mobile technologies enable new ways of learning. They offer us new possibilities to access an enormous amount of knowledge at any time and everywhere. Among many advantages, the adaptations require a rethinking of our previous learning behaviour patterns and processes. The challenge for students is no longer to get access to information and knowledge, but to select the right one and to deal with the information and knowledge overflow. The aim of this research is to define, design and validate an advanced concept to support the contemporary learning processes. Therefore, the requirements for a new approach have been assessed, the available solutions from the related area of (personal) Knowledge Management have been investigated, and the weaknesses in the context of learning identified. The identified issues have been substantiated by university students via a quantitative survey. Besides several smaller aspects, knowledge fragmentation and the nescience of the knowledge formation process have been classified as the most critical ones. To overcome these problems, a methodological concept has been developed, and a corresponding technological design created. The chosen approach is an intelligent, independent intermediate layer, which traces the different steps our knowledge entities are going through. Based on personal and individual configurations, the system provides a comprehensive and overall observation of nearly all our knowledge work activities. It supports the building and accessing of the knowledge formation paths for every important knowledge unit, later path combination and the access to automatically generated versions of our work. Moreover, it helps the users not only to remember what they did, but also gives them some strong indications why they did it. This is achieved by combining different knowledge actions and looking at the influences they have on each other. The suggested concept has been critically proved and confirmed via a qualitative expert analysis and backed up by a quantitative survey among university students.
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Loggenberg, Ernest Wilfred. "Teaching and learning electrostatics using everyday knowledge, indigenous knowledge and scientific argumentation." Thesis, Nelson Mandela Metropolitan University, 2012. http://hdl.handle.net/10948/d1008412.
Повний текст джерелаАнотація:
South African School Curriculum, calls for the integration of IKS within school science (Department of Education, 2006, Department of Basic Education, 2011). Lightning is an area of high interest in the Eastern Cape and is used as the topic in this study which focuses on the integration of indigenous knowledge systems in science education. The study investigated the impact of an intervention strategy framed around the use of scientific argumentation and the integration of everyday knowledge and indigenous knowledge systems (IKS) into the teaching of electrostatics at Grade Ten level. The impact focused on the teachers’ ability to implement the strategy, the electrostatics knowledge gained by learners, the learners’ argumentation ability, and the motivational and confidence levels of both teachers and learners. The sample comprised eight schools (the science teachers and their Grade Ten Physical Science learners) in the Uitenhage District of Education of the Eastern Cape Province of South Africa. Qualitative data were generated via interviews, classroom observations, pre- and post test questionnaires with open-ended questions to evoke meaningful responses that could not be anticipated by the research, and argumentation writing frames for both teachers and learners. Limited quantitative data were generated via the argumentation writing frames and the more close-ended questionnaire questions. The findings of the teacher and learner argumentation frames and the teacher checklists which revealed that the intervention impacted positively on the teachers’ ability to integrate IKS into their teaching practice. The use indigenous knowledge as the context for argumentation appears to have been a more effective way of introducing the concept than doing so within a scientific context (which the learners found difficult). The intervention facilitated an enhanced level of understanding on lightning, and assisted with the creation of the “third space” and border crossing between IKS and western science. The individual interviews disclosed the teachers’ improved ability to integrate IKS, IKS improving the facilitation of the argumentation strategy, and their improved motivation and confidence.
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Björkman, Oscar. "Meaning-making knowledge sharing : Learning aspects of a Sandvik knowledge management system." Thesis, KTH, Skolan för teknikvetenskaplig kommunikation och lärande (ECE), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-142647.
Повний текст джерелаАнотація:
The focus of this thesis is the KMS at a Sandvik design department. Purposed to deal with information overload using user-generated content, it is also intended to enable the employees to share knowledge. Previous research has studied what motivates employees to use technology for knowledge sharing. This study seeks beyond what is motivating and instead asks what it is that creates meaning for the employees in using and contributing to the KMS. Based on what is found to be meaning-making the thesis discusses and highlights design considerations for the KMS. Qualitative methods as well as theories on learning, motivation and meaning-making is used. Six employees were interviewed and the analysis suggests using thematization that what is meaning-making for the employee is linked with the approach towards work tasks. Meaning-making aspects is seen as either instrumental or social. The use of communicative and social features should be considered.I uppsatsens fokus står en kunskapsdelningsplattform på en av Sandvikskonstruktionsavdelningar. Plattformen ska med användargenererat innehåll underlätta informationssökning samt tillåta användarna att dela kunskap. Tidigare forskning har studerat vad som motiverar anställda att använda datorsystem till att dela kunskap. Denna uppsats söker bortom vad som motiverar och frågar istället vad det är som skapar mening för de anställda i att använda sig av och bidra till denna plattform. Utifrån detta diskuterar och föreslår uppsatsen designförslag till plattformen. Kvalitativa metoder samt teorier om lärande, motivation och meningsskapande används. Sex anställda intervjuades och i den efterföljande analysen som bestod av tematisering framkom det att vad som skapar mening för den anställde går hand i hand med hur denne ser sina arbetsuppgifter. De meningsskapande aspekterna betraktas som antingen instrumentella eller sociala. Användning av kommunikativa och sociala funktioner föreslås till utformningen av plattformen.
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Hasan, Irfan. "Machine learning techniques for automated knowledge acquisition in intelligent knowledge-based systems." Instructions for remote access. Click here to access this electronic resource. Access available to Kutztown University faculty, staff, and students only, 1991. http://www.kutztown.edu/library/services/remote_access.asp.
Повний текст джерелаАнотація:
Thesis (M.S.)--Kutztown University of Pennsylvania, 1991.Source: Masters Abstracts International, Volume: 45-06, page: 3187. Abstract precedes thesis as [2] preliminary leaves. Typescript. Includes bibliographical references (leaves 102-104).
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Tuovinen, L. (Lauri). "From machine learning to learning with machines:remodeling the knowledge discovery process." Doctoral thesis, Oulun yliopisto, 2014. http://urn.fi/urn:isbn:9789526205243.
Повний текст джерелаАнотація:
Abstract Knowledge discovery (KD) technology is used to extract knowledge from large quantities of digital data in an automated fashion. The established process model represents the KD process in a linear and technology-centered manner, as a sequence of transformations that refine raw data into more and more abstract and distilled representations. Any actual KD process, however, has aspects that are not adequately covered by this model. In particular, some of the most important actors in the process are not technological but human, and the operations associated with these actors are interactive rather than sequential in nature. This thesis proposes an augmentation of the established model that addresses this neglected dimension of the KD process. The proposed process model is composed of three sub-models: a data model, a workflow model, and an architectural model. Each sub-model views the KD process from a different angle: the data model examines the process from the perspective of different states of data and transformations that convert data from one state to another, the workflow model describes the actors of the process and the interactions between them, and the architectural model guides the design of software for the execution of the process. For each of the sub-models, the thesis first defines a set of requirements, then presents the solution designed to satisfy the requirements, and finally, re-examines the requirements to show how they are accounted for by the solution. The principal contribution of the thesis is a broader perspective on the KD process than what is currently the mainstream view. The augmented KD process model proposed by the thesis makes use of the established model, but expands it by gathering data management and knowledge representation, KD workflow and software architecture under a single unified model. Furthermore, the proposed model considers issues that are usually either overlooked or treated as separate from the KD process, such as the philosophical aspect of KD. The thesis also discusses a number of technical solutions to individual sub-problems of the KD process, including two software frameworks and four case-study applications that serve as concrete implementations and illustrations of several key features of the proposed process modelTiivistelmä Tiedonlouhintateknologialla etsitään automoidusti tietoa suurista määristä digitaalista dataa. Vakiintunut prosessimalli kuvaa tiedonlouhintaprosessia lineaarisesti ja teknologiakeskeisesti sarjana muunnoksia, jotka jalostavat raakadataa yhä abstraktimpiin ja tiivistetympiin esitysmuotoihin. Todellisissa tiedonlouhintaprosesseissa on kuitenkin aina osa-alueita, joita tällainen malli ei kata riittävän hyvin. Erityisesti on huomattava, että eräät prosessin tärkeimmistä toimijoista ovat ihmisiä, eivät teknologiaa, ja että heidän toimintansa prosessissa on luonteeltaan vuorovaikutteista eikä sarjallista. Tässä väitöskirjassa ehdotetaan vakiintuneen mallin täydentämistä siten, että tämä tiedonlouhintaprosessin laiminlyöty ulottuvuus otetaan huomioon. Ehdotettu prosessimalli koostuu kolmesta osamallista, jotka ovat tietomalli, työnkulkumalli ja arkkitehtuurimalli. Kukin osamalli tarkastelee tiedonlouhintaprosessia eri näkökulmasta: tietomallin näkökulma käsittää tiedon eri olomuodot sekä muunnokset olomuotojen välillä, työnkulkumalli kuvaa prosessin toimijat sekä niiden väliset vuorovaikutukset, ja arkkitehtuurimalli ohjaa prosessin suorittamista tukevien ohjelmistojen suunnittelua. Väitöskirjassa määritellään aluksi kullekin osamallille joukko vaatimuksia, minkä jälkeen esitetään vaatimusten täyttämiseksi suunniteltu ratkaisu. Lopuksi palataan tarkastelemaan vaatimuksia ja osoitetaan, kuinka ne on otettu ratkaisussa huomioon. Väitöskirjan pääasiallinen kontribuutio on se, että se avaa tiedonlouhintaprosessiin valtavirran käsityksiä laajemman tarkastelukulman. Väitöskirjan sisältämä täydennetty prosessimalli hyödyntää vakiintunutta mallia, mutta laajentaa sitä kokoamalla tiedonhallinnan ja tietämyksen esittämisen, tiedon louhinnan työnkulun sekä ohjelmistoarkkitehtuurin osatekijöiksi yhdistettyyn malliin. Lisäksi malli kattaa aiheita, joita tavallisesti ei oteta huomioon tai joiden ei katsota kuuluvan osaksi tiedonlouhintaprosessia; tällaisia ovat esimerkiksi tiedon louhintaan liittyvät filosofiset kysymykset. Väitöskirjassa käsitellään myös kahta ohjelmistokehystä ja neljää tapaustutkimuksena esiteltävää sovellusta, jotka edustavat teknisiä ratkaisuja eräisiin yksittäisiin tiedonlouhintaprosessin osaongelmiin. Kehykset ja sovellukset toteuttavat ja havainnollistavat useita ehdotetun prosessimallin merkittävimpiä ominaisuuksia
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Vavoula, Giasemi. "KLeOS : a knowledge and learning system in support of lifelong learning." Thesis, University of Birmingham, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.402432.
Повний текст джерела
42
Mao, Yi. "Domain knowledge, uncertainty, and parameter constraints." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37295.
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Yan, Mo-lan. "Knowledge building in project-based science learning." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B31598687.
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Maung, Aung Soe Paing. "Hybrid knowledge-based support with learning abilities." Thesis, University of Macau, 1997. http://umaclib3.umac.mo/record=b1636984.
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45
Blackman, Deborah. "How learning organisation practices close knowledge creation." Thesis, Southampton Solent University, 2002. http://ssudl.solent.ac.uk/617/.
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Suryanto, Hendra Computer Science & Engineering Faculty of Engineering UNSW. "Learning and discovery in incremental knowledge acquisition." Awarded by:University of New South Wales. School of Computer Science and Engineering, 2005. http://handle.unsw.edu.au/1959.4/20744.
Повний текст джерелаАнотація:
Knowledge Based Systems (KBS) have been actively investigated since the early period of AI. There are four common methods of building expert systems: modeling approaches, programming approaches, case-based approaches and machine-learning approaches. One particular technique is Ripple Down Rules (RDR) which may be classified as an incremental case-based approach. Knowledge needs to be acquired from experts in the context of individual cases viewed by them. In the RDR framework, the expert adds a new rule based on the context of an individual case. This task is simple and only affects the expert???s workflow minimally. The rule added fixes an incorrect interpretation made by the KBS but with minimal impact on the KBS's previous correct performance. This provides incremental improvement. Despite these strengths of RDR, there are some limitations including rule redundancy, lack of intermediate features and lack of models. This thesis addresses these RDR limitations by applying automatic learning algorithms to reorganize the knowledge base, to learn intermediate features and possibly to discover domain models. The redundancy problem occurs because rules created in particular contexts which should have more general application. We address this limitation by reorganizing the knowledge base and removing redundant rules. Removal of redundant rules should also reduce the number of future knowledge acquisition sessions. Intermediate features improve modularity, because the expert can deal with features in groups rather than individually. In addition to the manual creation of intermediate features for RDR, we propose the automated discovery of intermediate features to speed up the knowledge acquisition process by generalizing existing rules. Finally, the Ripple Down Rules approach facilitates rapid knowledge acquisition as it can be initialized with a minimal ontology. Despite minimal modeling, we propose that a more developed knowledge model can be extracted from an existing RDR KBS. This may be useful in using RDR KBS for other applications. The most useful of these three developments was the automated discovery of intermediate features. This made a significant difference to the number of knowledge acquisition sessions required.
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Grant, Timothy John. "Inductive learning of knowledge-based planning operators." [Maastricht : Maastricht : Rijksuniversiteit Limburg] ; University Library, Maastricht University [Host], 1996. http://arno.unimaas.nl/show.cgi?fid=6686.
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Yan, Mo-lan, and 甄慕蘭. "Knowledge building in project-based science learning." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B31598687.
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Tang, M. X. "Knowledge-based design support and inductive learning." Thesis, University of Edinburgh, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.662724.
Повний текст джерелаАнотація:
In order to incorporate inductive learning techniques into a knowledge-based design model and an integrated knowledge-based design support system architecture, the computational techniques for developing a knowledge-based design support system architecture and the role of inductive learning in AI-based design are investigated. This investigation gives a background to the development of an incremental learning model for design suitable for a class of design tasks whose structures are not well known initially. This incremental learning model for design is used as a basis to develop knowledge-based design support system architecture that can be used as a kernel for knowledge-based design applications. This architecture integrates a number of computational techniques to support the representation and reasoning of design knowledge. In particular, it integrates a blackboard control system with an assumption-based truth maintenance system in an object-oriented environment to support the exploration of multiple design solutions by supporting the exploration and management of design contexts. As an integral part of this knowledge-based design support architecture, a design concept learning system utilising a number of unsupervised inductive learning techniques is developed. This design concept learning system combines concept formation techniques with design heuristics as background knowledge to build a design concept tree from raw data or past design examples. The effectiveness of this knowledge-based design support architecture and the design concept learning system is demonstrated through a realistic design domain, the design of small-molecule drugs one of the key tasks of which is to identify a pharmacophore description (the structure of a design problem) from known molecule examples. In this thesis, knowledge-based design and inductive learning techniques are first reviewed. Based on this review, an incremental learning model and an integrated architecture for intelligent design support are presented.
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Bott, Lewis Andrew. "Prior knowledge and statistical models of learning." Thesis, University of Warwick, 2001. http://wrap.warwick.ac.uk/3075/.
Повний текст джерелаАнотація:
The research reported here describes the effects of prior knowledge on how people form categories and learn continuous mappings. Chapter 2 is a review of the past research on knowledge effects in the statistical and psychological literature. Chapter 3 presents simulations of a set of experiments carried out by Heit and Bott (2000) into how knowledge is selected in a category learning task. The model was shown to account for the results of Heit and Bott and generate several new predictions concerning blocking effects with the use of prior knowledge. However, empirical testing of these predictions failed to demonstrate these effects. Chapter 4 describes work testing Delosh, McDaniel and Busemeyer's (1997) model of function learning, the Extrapolation Associative Learning Model (EXAM). Experiments were carried out demonstrating that a model that assumes only linear extrapolation, such as EXAM, is inadequate as a generic model of function learning. An alternative model to EXAM is presented which is constructed of several components, each module applying different quantities of prior knowledge to the task. Chapter 5 presents experiments investigating the extent to which participants abstract and apply functions in transfer-tasks. The results demonstrate that models of function learning must be able to restrict their range of allowable solutions in psychologically plausible ways.