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Dissertations / Theses on the topic 'Knowledge acquisition'
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Al-Jabir, Shaikha. "Terminology-based knowledge acquisition." Thesis, University of Surrey, 1999. http://epubs.surrey.ac.uk/843300/.
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A methodology for knowledge acquisition from terminology databases is presented. The methodology outlines how the content of a terminology database can be mapped onto a knowledge base with a minimum of human intervention. Typically, terms are defined and elaborated by terminologists by using sentences that have a common syntactic and semantic structure. It has been argued that in defining terms, terminologists use a local grammar and that this local grammar can be used to parse the definitions. The methodology has been implemented in a program called DEARSys (Definition Analysis and Representation System), that reads definition sentences and extracts new concepts and conceptual relations about the defined terms. The linguistic component of the system is a parser for the sublanguage of terminology definitions that analyses a definition into its logical form, which in turn is mapped onto a frame-based representation. The logical form is based on first-order logic (FOL) extended with untyped lambda calculus. Our approach is data-driven and domain independent; it has been applied to definitions of various domains. Experiments were conducted with human subjects to evaluate the information acquired by the system. The results of the preliminary evaluation were encouraging.
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Youn, Bong-Soo. "Intelligent knowledge acquisition system /." Online version of thesis, 1989. http://hdl.handle.net/1850/10444.
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González-Fernández, Beatriz. "Vocabulary knowledge components : knowledge, acquisition and conceptualisation." Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/52090/.
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Vocabulary knowledge is a multifaceted construct for which complete command comprises mastering various types of knowledge. Achieving this full mastery is deemed challenging and problematic for second language learners, and yet it is key for successful and appropriate language use (Webb & Nation, 2017). By understanding how these various kinds of knowledge behave and relate, practitioners can better systematise when and how they are introduced to the students, and thus facilitate the overall vocabulary learning process. Nevertheless, little is known about how these multiple types of word knowledge are acquired by learners of a second/foreign language. This thesis attempts to contribute to bridging this gap by empirically exploring the knowledge, acquisition and conceptualisation of overall vocabulary knowledge in second languages. Five studies are devoted to this aim. Study 1 examined the knowledge and order of acquisition of four different components of vocabulary knowledge (form–meaning link, collocations, derivatives and multiple meanings) in recall and recognition. It shows that those components vary considerably in their difficulty for second language (L2) learners, and implicational scaling analysis revealed that a consistent order of acquisition of these components can be established. Study 2 investigated how various factors typically identified as influencing vocabulary learning affect the mastery of those four word knowledge components. The results suggest that cognateness status of the target words has the strongest effect on knowledge of most vocabulary aspects by Spanish learners of L2 English, followed by frequency and proficiency. Importantly, this cognate influence raised the question of whether the order of acquisition of word knowledge components retrieved in Study 1 was unique to L2 English learners of cognate languages. Study 3 explored the theoretical conceptualisation of vocabulary knowledge by attempting to provide empirical support for its multidimensionality. Structural equation modelling analyses exposed that the various types of vocabulary knowledge were so interconnected that they could not be considered separate dimensions. This finding suggests that the different aspects of vocabulary knowledge are better seen as various word knowledge difficulty levels that comprise a unidimensional construct. Finally, Studies 4 and 5 tried to provide generalisability to the previous findings by replicating Studies 1 and 3, respectively, with Chinese L2 learners of English. Study 4 investigated the hypothesis that the order of acquisition outlined in Study 1 for Spanish learners depended partially on the cognate status of the participants’ language. The implicational scaling analysis with the non-cognate Chinese population, however, corroborated the order of acquisition of vocabulary aspects previously suggested, indicating that a universal vocabulary acquisition order might exist. Study 5 also confirmed the finding that vocabulary knowledge is not empirically multidimensional. In addition, it provided evidence for the fact that the vocabulary knowledge construct functions similarly across the Chinese and Spanish learners of English as a unidimensional concept. Taken together, the results presented in this thesis support the notion that mastering the various components involved in word knowledge is a slow and incremental process, and demonstrate that some of them seem to be consistently acquired before others. Nonetheless, the findings also suggest that these different types of word knowledge cannot be considered separate dimensions in the learners’ mental lexicon, and thereby the multidimensional structure of vocabulary knowledge might need to be reconsidered. Overall, while more research is needed, these findings offer useful insights for the learning and teaching of vocabulary in a more systematic and efficient manner.
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Bakke, Elise. "Knowledge acquisition and modelling for knowledge-intensive CBR." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2005. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9187.
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This thesis contains a study of state of the art knowledge acquisition modelling principles and methods for modelling general domain knowledge. This includes Newell's knowledge level, knowledge level modelling, Components of Expertise, CommonKADS and the Protégé meta tool. The thesis also includes a short introduction to the knowledge-intensive case-based reasoning system TrollCreek. Based on this background knowledge, one did analysis and comparison of different possible solutions. Then, after justifying the choices made, a knowledge acquisition method for TrollCreek was created. The method was illustrated through an example, evaluated and discussed.
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Jones, Hugh William Fawcett. "Children's understanding of knowledge acquisition." Thesis, University of Oxford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306994.
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Wu, Xindong. "Knowledge acquisition from data bases." Thesis, University of Edinburgh, 1993. http://hdl.handle.net/1842/581.
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Knowledge acquisition from databases is a research frontier for both data base technology and machine learning (ML) techniques,and has seen sustained research over recent years. It also acts as a link between the two fields,thus offering a dual benefit. Firstly, since database technology has already found wide application in many fields ML research obviously stands to gain from this greater exposure and established technological foundation. Secondly, ML techniques can augment the ability of existing database systems to represent acquire,and process a collection of expertise such as those which form part of the semantics of many advanced applications (e.gCAD/CAM).The major contribution of this thesis is the introduction of an effcient induction algorithm to facilitate the acquisition of such knowledge from databases. There are three typical families of inductive algorithms: the generalisation- specialisation based AQ11-like family, the decision tree based ID3-like family,and the extension matrix based family. A heuristic induction algorithm, HCV based on the newly-developed extension matrix approach is described in this thesis. By dividing the positive examples (PE) of a specific class in a given example set into intersect in groups and adopting a set of strategies to find a heuristic conjunctive rule in each group which covers all the group's positiv examples and none of the negativ examples(NE),HCV can find rules in the form of variable-valued logic for PE against NE in low-order polynomial time. The rules generated in HCV are shown empirically to be more compact than the rules produced by AQ1-like algorithms and the decision trees produced by the ID3-like algorithms. KEshell2, an intelligent learning database system, which makes use of the HCV algorithm and couples ML techniques with database and knowledgebase technology, is also described.
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Muggleton, Stephen H. "Inductive acquisition of expert knowledge." Thesis, University of Edinburgh, 1986. http://hdl.handle.net/1842/8124.
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Expert systems divide neatly into two categories: those in which ( 1) the expert decisions result in changes to some external environment (control systems), and (2) the expert decisions merely seek to describe the environment (classification systems). Both the explanation of computer-based reasoning and the "bottleneck" (Feigenbaum, 1979) of knowledge acquisition are major issues in expert systems research. We have contributed to these areas of research in two ways. Firstly, we have implemented an expert system shell, the Mugol environment, which facilitates knowledge acquisition by inductive inference and provides automatic explanation of run-time reasoning on demand. RuleMaster, a commercial version of this environment, has been used to advantage industrially in the construction and testing of two large classification systems. Secondly, we have investigated a new technique called sequence induction which can be used in the construction of control systems. Sequence induction is based on theoretical work in grammatical learning. We have improved existing grammatical learning algorithms as well as suggesting and theoretically characterising new ones. These algorithms have been successfully applied to the acquisition of knowledge for a diverse set of control systems, including inductive construction of robot plans and chess end-game strategies.
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Chisnall, Anne Clare. "Grounded theory for knowledge acquisition." Thesis, De Montfort University, 1998. http://hdl.handle.net/2086/4140.
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Thomas, Christopher J. "Knowledge Acquisition in a System." Wright State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=wright1357753287.
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Bosan, Sorel. "Interactive Simulations for Knowledge Acquisition." W&M ScholarWorks, 1989. https://scholarworks.wm.edu/etd/1539626819.
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Ward, Antony. "Acquisition of service product knowledge." Thesis, Queensland University of Technology, 1995.
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Chan, Christine Wai-Chi. "An empirical investigation of knowledge acquisition." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/27688.
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Expert systems are being developed despite the widely acknowledged problem of acquiring knowledge from experts. This study attempts to understand how knowledge acquisition is conducted in practice by investigating three expert system development projects. The variables examined include the expert, knowledge engineer, problem domain, organizational setting, the knowledge acquisition process, the expert system construction process, and the expert system itself. A case research methodology is adopted and data is collected through observation and taped protocol of knowledge acquisition sessions, post facto interviews with the participants involved, journalistic accounts kept by the subjects, and deliverables produced. Three cases on expert systems built in the domains of law of negligence, telephone line fault diagnostic, and wastewater treatment have been investigated. By juxtaposing the observations drawn from these cases with the findings reported in the literature, this inquiry contributes to the current understanding of the knowledge acquisition process.Business, Sauder School of
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Mase, Kenji, Shoji Kajita, Yasushi Hirano, Takuya Maekawa, and Shohei Yoshioka. "Interactive Story Creation for Knowledge Acquisition." IEEE, 2010. http://hdl.handle.net/2237/14446.
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Pfister, Alex. "Unsupervised acquisition of concatenative morphological knowledge." Thesis, Imperial College London, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.393689.
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Williams, Ryan Duane. "ComicKit : knowledge acquisition of story scripts." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/33388.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (leaves 50-51).
The field of Artificial Intelligence stands poised to make great leaps in emulating human intelligence. The development of a way to acquire and use common sense is the key to this advancement. This thesis describes the design and construction of ComicKit, a tool for acquiring story scripts for a common sense knowledge base. ComicKit's core mechanism is dragging and dropping icons into the panels of a comic. As the user creates a comic, ComicKit makes common sense suggestions for the story. ComicKit follows on the successful model of Open Mind Common Sense, a web-based activity that thousands of people around the world contributed bits of common sense knowledge to. It is hoped that many people will contribute a few hundred thousand stories through ComicKit, and build a large corpus of common sense story knowledge.
by Ryan Duane Williams.
M.Eng.
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Lei, Tao Ph D. Massachusetts Institute of Technology. "Domain knowledge acquisition via language grounding." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/82412.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 54-60).
This thesis addresses the language grounding problem at the level of word relation extraction. We propose methods to acquire knowledge represented in the form of relations and utilize them in two domain applications, high-level planning in a complex virtual world and input parser generation from input format specifications. In the first application, we propose a reinforcement learning framework to jointly learn to predict precondition relations from text and to perform high-level planning guided by those relations. When applied to a complex virtual world and text describing that world, our relation extraction technique performs on par with a supervised baseline, and we show that a high-level planner utilizing these extracted relations significantly outperforms a strong, text unaware baseline. In the second application, we use a sampling framework to predict relation trees and to generate input parser code from those trees. Our results show that our approach outperforms a state-of-the-art semantic parser on a dataset of input format specifications from the ACM International Collegiate Programming Contest, which were written in English for humans with no intention of providing support for automated processing.
by Tao Lei.
S.M.
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White, Simon. "Enhancing knowledge acquisition with constraint technology." Thesis, University of Aberdeen, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.322633.
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Kirkgöz, Yasemín. "Knowledge acquisition from L2 specialist texts." Thesis, Aston University, 1999. http://publications.aston.ac.uk/15191/.
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This research aims to investigate knowledge acquisition and concept formation in the domain of economics and business studies through a foreign language, English, from the very initial to the very final stage of development in the context of Higher Education in Turkey. It traces both the processes as well as the product of acquisition in order to provide a detailed picture of how knowledge acquisition occurs. It aims to explore ways in which the acquisition process can be facilitated and promoted while prospective students of the Department of Economics and Business Administration receive a language training programme, following the completion of which they will join their academic community which offers part of its courses through the English language. The study draws upon (some) theories of mental representation of knowledge, such as schema, frame and script. The concept of discourse community with its characteristics is investigated, enculturation of prospective students to acquire knowledge of their domain through L2 is explored, and the crucial role of the constructivist theory in relation to knowledge acquisition is highlighted. The present study was conducted through a process of enculturation taking place partly at the language centre of Çukurova University and partly at the target discourse community. The data utilised for initiating knowledge acquisition was obtained by establishing a corpus of economics and business texts, which the learners are expected to read during their academic courses utilising computerised technology. The method of think aloud protocols was used to analyse processes taking place in knowledge acquisition, while the product of what was acquired was investigated by means of written recall protocols. It has been discovered that knowledge acquisition operates on the basis of analogical and to a certain extent metaphorical reasoning. The evidence obtained from the think aloud protocols showed that neophytes were able to acquire fundamental concepts of their future domain by reaching the level of shared understanding with the members of their target community of the faculty. Diaries and questionnaire analyses demonstrated that enculturation facilitated learners' transition from the language centre into the target community. Analyses of the written recall protocols and examinations from the post-enculturation stage of the research showed that neophytes' academic performances in their target community were much higher than those of their non-enculturated counterparts. Processes learners go through and strategies they spontaneously make use of, especially while acquiring knowledge of a specific domain through L2 have so far remained unexplored research areas. The present research makes a potential contribution to the language and knowledge acquisition theories by examining closely and systematically the language and the strategies they employ in acquiring such knowledge. The research findings offer useful implications to English language teaching at language schools. Language teachers are provided with useful guidelines as to how they can provide prospective students of a particular academic community with an experience of acquiring fundamental concepts of their discipline before they become members of their target community.
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Sharma, Sunil. "Case based knowledge acquisition and refinement." Thesis, University of Aberdeen, 1988. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU021146.
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This thesis reports research undertaken in two rather distinct phases. Firstly, the thesis reports a study of cognitive processes involved in the task of 'concept identification': given sample instances of a concept, the task is to identify the concept. A computer model which successfully reproduces responses similar to those observed in human subjects is described. Secondly, this thesis reports the design of a case-based learning system REFINER. The system is a 'Learning Apprentice System' for differential diagnosis tasks, to aid the transfer of knowledge from a domain expert to a computer. Knowledge is obtained from the expert(s) in the form of cases which have been diagnosed or classified, and not in the traditional form of classification 'rules' which the experts often find hard to specify. The REFINER program is therefore a Knowledge Acquisiton System which helps an expert refine his knowledge in a more 'natural' way than having rules 'extracted'. Further, the system has the ability to point out that two classifications are not distinct, and can then suggest to the user ways in which the inconsistency might be resolved. Although the system has been used most extensively in the medical domain, it is essentially domain independent.
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Garnier, Mélodie. "English phrasal verbs : usage, knowledge, acquisition." Thesis, University of Nottingham, 2016. http://eprints.nottingham.ac.uk/38662/.
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Formulaic language constitutes an essential part of English vocabulary and is necessary for performing a wide range of communicative functions, but knowledge and acquisition of formulaic sequences is typically found to be lacking and problematic for L2 learners. Whilst much research has been carried out on formulaic sequences such as idioms and collocations, comparatively little has been done on phrasal verbs which are nonetheless commonly perceived as one of the most challenging aspects of English vocabulary. This thesis attempts to contribute to filling this gap by exploring the usage, knowledge and acquisition of phrasal verbs by native and non-native speakers of English. Study 1 explores the semantic frequencies of the 150 most frequently used phrasal verbs using the Corpus of Contemporary American English (COCA). Results show that, whilst the vast majority of these phrasal verbs are polysemous, only two meaning senses on average are enough to cover three-quarters of the occurrences of each of them. The most frequent meaning senses of all 150 phrasal verbs are listed in the PHrasal VErb pedagogical List (PHaVE List), in frequency ranking order along with frequency percentages. The list thus offers teachers and learners the possibility of prioritising these most frequent, and thus most important, meaning senses, thereby allowing for a more systematic approach to tackling phrasal verbs. Study 2 explores L2 learners’ knowledge of a sample of phrasal verbs and meaning senses on the PHaVE List at a form-recall level of mastery, and the effect of a number of factors on this knowledge. Results show that only about 40 % of meaning senses were known, with a 20 % chance that all the various meaning senses attached to a given phrasal verb would be known. A mixed-effect modelling analysis reveals a significant effect of two factors on scores: item frequency and learner engagement in leisure activities in the L2 such as reading and social networking. This is consistent with previous research showing the robust effect of frequency for L2 knowledge of individual words and formulaic sequences, and the benefits of reading for L2 language acquisition. Study 3 investigates L2 learners’ acquisition of novel phrasal verbs through three intentional, word-focused learning activities: rote memorisation, textbook exercises, and guessing from context. Knowledge of the items was measured both immediately and one week after the teaching treatment at meaning-recall and meaning-recognition levels of mastery. Results show encouraging learning gains, similar to those found by previous research for individual words and idioms, with higher L2 proficiency and general vocabulary knowledge leading to significantly higher scores. A Friedman test reveals no significant difference in learning gains between the three activities. Taken together, these studies provide empirical evidence for the gap in L2 learners’ knowledge of phrasal verbs, but suggest that a restricted number of phrasal verbs and meaning senses can go a long way and be effectively learned using the same explicit activities commonly used for learning single words. Overall, they offer useful insights for learning and teaching English phrasal verbs in a more systematic and efficient manner.
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Macy, Robert Scott. "Knowledge competency acquisition in the knowledge economy : links to firm performance /." view abstract or download file of text, 2006. http://proquest.umi.com/pqdweb?did=1196407371&sid=1&Fmt=2&clientId=11238&RQT=309&VName=PQD.
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Thesis (Ph. D.)--University of Oregon, 2006.Typescript. Includes vita and abstract. Study based on data derived from a sampling of 189 large U.S. law firms. Includes bibliographical references (leaves 90-101). Also available for download via the World Wide Web; free to University of Oregon users.
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Kang, Seung Hwan. "Intelligent knowledge acquisition using case-based reasoning knowledge sharing and reuse /." Access electronically, 2003. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20050310.145300/index.html.
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Luzzi, Federico Walter. "Knowledge from ignorance : a study in the acquisition of inferential knowledge." Thesis, University of Aberdeen, 2010. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=165819.
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The view that knowledge-yielding single-premise deductive inference must proceed from a known premise is very plausible at first blush. In this thesis I explore in detail the possibility that this view is false. I construct a series of challenging cases against the principle of Counter-Closure, which expresses this view. These cases force theorists endorsing a variety of contemporary views to either (i) abandon Counter-Closure; (ii) admit into their epistemology novel and theory-specific kinds of Gettier cases; or (iii) make significant revisions to their theories. I offer considerations that help would-be deniers of Counter-Closure explain away its prima facie plausibility and suggest a suitable theoretical replacement phrased in terms of justification rather than knowledge. Finally, I connect this discussion with debates in the epistemologies of testimony and memory, where analogue principles to Counter- Closure have been recently subjected to critical scrutiny.
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Pham, Son Bao Computer Science & Engineering Faculty of Engineering UNSW. "Incremental knowledge acquisition for natural language processing." Awarded by:University of New South Wales. School of Computer Science and Engineering, 2006. http://handle.unsw.edu.au/1959.4/26299.
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Linguistic patterns have been used widely in shallow methods to develop numerous NLP applications. Approaches for acquiring linguistic patterns can be broadly categorised into three groups: supervised learning, unsupervised learning and manual methods. In supervised learning approaches, a large annotated training corpus is required for the learning algorithms to achieve decent results. However, annotated corpora are expensive to obtain and usually available only for established tasks. Unsupervised learning approaches usually start with a few seed examples and gather some statistics based on a large unannotated corpus to detect new examples that are similar to the seed ones. Most of these approaches either populate lexicons for predefined patterns or learn new patterns for extracting general factual information; hence they are applicable to only a limited number of tasks. Manually creating linguistic patterns has the advantage of utilising an expert's knowledge to overcome the scarcity of annotated data. In tasks with no annotated data available, the manual way seems to be the only choice. One typical problem that occurs with manual approaches is that the combination of multiple patterns, possibly being used at different stages of processing, often causes unintended side effects. Existing approaches, however, do not focus on the practical problem of acquiring those patterns but rather on how to use linguistic patterns for processing text. A systematic way to support the process of manually acquiring linguistic patterns in an efficient manner is long overdue. This thesis presents KAFTIE, an incremental knowledge acquisition framework that strongly supports experts in creating linguistic patterns manually for various NLP tasks. KAFTIE addresses difficulties in manually constructing knowledge bases of linguistic patterns, or rules in general, often faced in existing approaches by: (1) offering a systematic way to create new patterns while ensuring they are consistent; (2) alleviating the difficulty in choosing the right level of generality when creating a new pattern; (3) suggesting how existing patterns can be modified to improve the knowledge base's performance; (4) making the effort in creating a new pattern, or modifying an existing pattern, independent of the knowledge base's size. KAFTIE, therefore, makes it possible for experts to efficiently build large knowledge bases for complex tasks. This thesis also presents the KAFDIS framework for discourse processing using new representation formalisms: the level-of-detail tree and the discourse structure graph.
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Khan, Abdus Salam Computer Science & Engineering Faculty of Engineering UNSW. "Incremental knowledge acquisition for case-based reasoning." Awarded by:University of New South Wales. School of Computer Science and Engineering, 2003. http://handle.unsw.edu.au/1959.4/19376.
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Case-Based Reasoning (CBR) is an appealing technique for developing intelligent systems. Besides its psycho- logical plausibility and a substantial body of research during recent years, building a good CBR system remains still a difficult task. The main problems remaining are the development of suitable case retrieval and adaptation mechanisms for CBR. The major issues are how and when to capture the necessary knowledge for both of the above aspects. As a contribution to knowledge this thesis proposes a new approach to address the experienced difficulties. The basic framework of Ripple Down Rules (RDR) is extended to allow the incremental development of a knowledge base for each of the two functions: case retrieval and case adaptation, during the use of the system while solving actual problems. The proposed approach allows an expert-user to provide explanations of why, for a given problem, certain actions should be taken. Incrementally knowledge is acquired from the expert-user in which the expert refines a rule which performs unsatisfactorily for a current given problem. The approach facilitates both, the rule acquisition as well as its validation. As a result the knowledge maintenance task of a knowledge engineer is overcome. This approach is effective with respect to both, the development of highly tailored and complex retrieval and adaptation functions for CBR as well as the provision of an intuitive and feasible approach for the expert. The approach has been implemented in a CBR system named MIKAS (Menu Construction using Incre- mental Knowledge Acquisition Systems) for the design of menus (diets) according to dietary requirements. The experimental evidence indicates the suitability of the approach to address the retrieval and adaptation problems of the menu construction domain. The experimental evidence also indicates that the difficulties of developing retrieval and adaptation functions for CBR can be effectively overcome by the proposed new approach. It is expected that the approach is likely to be useful in other problem solving domains where expert intervention is Required to modify a solution.
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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.
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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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Rydell, Karlsson Monica. "Knowledge acquisition in patients with heart disease /." Stockholm : Karolinska institutet, 2007. http://diss.kib.ki.se/2007/978-91-7357-257-6/.
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Trimble, John. "Knowledge acquisition and the system dynamics methodology." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/23337.
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Guo, Runli. "Proper name knowledge acquisition for text understanding." Thesis, University of Surrey, 2002. http://epubs.surrey.ac.uk/800039/.
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Wusteman, Judith. "EBKAT : an explanation-based knowledge acquisition tool." Thesis, University of Exeter, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.280682.
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Koh, Glenn. "Training spatial knowledge acquisition using virtual environments." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/43518.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (leaves 104-105).
by Glenn Koh.
M.Eng.
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Stange, Dominic, Andreas Nürnberger, and Holger Heyn. "Collaborative Knowledge Acquisition and Explorationin Technology Search." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-181723.
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This article is about technology search as an example of a knowledge acquisition task in industry. Technology search is about finding technology related information in structured as well as unstructured sources. This information is needed to support optimal decision making in business processes. There are new opptortunities for technology search and challenges that need to be addressed. This article outlines some of these challenges and presents two concepts to address them in a search system.
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Mitchell, F. "Painless knowledge acquisition for time series data." Thesis, University of Aberdeen, 1997. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU100889.
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Knowledge Acquisition has long been acknowledged as the bottleneck in producing Expert Systems. This is because, until relatively recently, the KA (Knowledge Acquisition) process has concentrated on extracting knowledge from a domain expert, which is a very time consuming process. Support tools have been constructed to help this process, but these have not been able to reduce the time radically. However, in many domains, the expert is not the only source of knowledge, nor indeed the best source of knowledge. This is particularly true in industrial settings where performance information is routinely archived. This information, if processed correctly, can provide a substantial part of the knowledge required to build a KB (Knowledge Base). In this thesis I discuss current KA approaches and then go on to outline a methodology which uses KD (Knowledge Discovery) techniques to mine archived time series data to produce fault detection and diagnosis KBs with minimal expert input. This methodology is implemented in the TIGON system, which is the focus of this thesis. TIGON uses archived information (in TIGON's case the information is from a gas turbine engine) along with guidance from the expert to produce KBs for detecting and diagnosing faults in a gas turbine engine. TIGON's performance is also analysed in some detail. A comparison with other related work is also included.
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Andrus, Jon Michael. "The acquisition of task-relevant audit knowledge." Diss., The University of Arizona, 1996. http://hdl.handle.net/10150/290577.
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It is widely held that the auditor's experience is the most important factor leading to the development and organization of the auditor's knowledge base (Waller and Felix 1984; Gibbins 1984). This study extends prior research by examining knowledge differences between auditors with similar amounts of public accounting experience (general domain experience) but with differing specific audit experiences and training. The study examines the association between experience and training and the auditors knowledge of the effectiveness of internal control and audit procedures to prevent and detect potential misstatements of financial statements. This particular knowledge is important in the performance of audit risk assessment and audit planning tasks. Risk assessment and audit planning tasks are important tasks that auditors begin to perform early in their auditing careers. In order to test these relationships, 60 subjects with approximately one to two years of public accounting experience performed a knowledge retrieval task to assess their knowledge of the relationship between common financial statement misstatements and the control and audit procedures that would prevent or detect those misstatements. Self-reported measures of public accounting experience and estimates of experience and training relevant to various industries and audit activities were collected to develop measures of task-relevant experience and training. The resulting evidence of this study provides limited support that differences in audit-cycle experience results in differences in the auditor's knowledge of effective internal control procedures. The study also provides evidence that the knowledge of the relationships between internal control and audit procedures and potential misstatements to financial statements is acquired, at least in part, prior to obtaining significant experience in performing audit planning tasks.
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Parsons, John Scott. "Automated knowledge acquisition for knowledge-based systems, KE-RIT : the Use of Kelleys' personal construct theory in the automation of knowledge acquisitions (theory and prototype) /." Online version of thesis, 1992. http://hdl.handle.net/1850/11056.
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Klijn, Elko. "Knowledge transfer between partners of international joint ventures : knowledge acquisition, knowledge accession, and eloquent capacity." Thesis, University of Leeds, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.428264.
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Corsar, David. "Developing knowledge-based systems through ontology mapping and ontology guided knowledge acquisition." Thesis, Available from the University of Aberdeen Library and Historic Collections Digital Resources, 2009. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?application=DIGITOOL-3&owner=resourcediscovery&custom_att_2=simple_viewer&pid=25800.
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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.
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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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Nicholson, Clive. "Knowledge acquisition for knowledge-based systems : an empirical comparison of two methods." Thesis, University of Southampton, 1992. https://eprints.soton.ac.uk/425631/.
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Mendes, David. "Clinical Practice Knowledge Acquisition and Interrogation using Natural Language." Doctoral thesis, Universidade de Évora, 2014. http://hdl.handle.net/10174/12553.
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The scientific concepts, methodologies and tools in the Knowledge Representation (KR) sub-
domain of applied Artificial Intelligence (AI) came a long way with enormous strides in recent
years. The usage of domain conceptualizations that are Ontologies is now powerful enough to aim
at computable reasoning over complex realities.
One of the most challenging scientific and technical human endeavors is the daily Clinical Prac-
tice (CP) of Cardiovascular (CV) specialty healthcare providers.
Such a complex domain can benefit largely from the possibility of clinical reasoning aids that are now
at the edge of being available.
We research into a complete end-to-end solid ontological infrastructure for CP knowledge represen-
tation as well as the associated processes to automatically acquire knowledge from clinical texts and
reason over it.
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Hashimoto, Chikara. "Knowledge Acquisition from the Web for Text Understanding." 京都大学 (Kyoto University), 2011. http://hdl.handle.net/2433/151931.
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Jordon, Lester Arlington. "Automating knowledge acquisition and representation with fuzzy logic." Thesis, University of British Columbia, 1991. http://hdl.handle.net/2429/29990.
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An interactive computer program has been developed to automate the construction of knowledge bases in expert system development. The program incorporates many user friendly features which allow users who may not understand the concepts of fuzzy logic or the complexity of the knowledge acquisition process to develop useful and complete Expert Systems.
Expert systems formalism are being successfully used in the industry. A major bottleneck in development of these systems lies in the knowledge acquisition phase. This study presents an induction system, based on fuzzy logic, which successfully automates the knowledge acquisitions process when the domain knowledge is embodied within discrete numerical data.
A tabloid database representing some desired input/output relationship is input to the system. Fuzzy expressions such as "high", "low" or "large" are either created automatically by the system or described explicitly by the user. These fuzzy expressions are automatically associated into an accurate and minimum rule set which models the desired input/output relationship.
The system was tested on the development of a knowledge base for a secondary crusher controller and a second more complex non-monotonic input/output relationship. In the controller example the knowledge bases developed were simpler, more accurate and built much faster than using a traditional interview approach. The non-monotonic relationship was also accurately described by a simple knowledge base.Applied Science, Faculty of
Mining Engineering, Keevil Institute of
Graduate
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Finlayson, Angela Margaret Computer Science & Engineering Faculty of Engineering UNSW. "Incremental knowledge acquisition for complex multi-agent environments." Publisher:University of New South Wales. Computer Science & Engineering, 2008. http://handle.unsw.edu.au/1959.4/42887.
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This thesis presents an incremental knowledge acquisition framework that supports the creation of multi-agent teams in complex real-time environments. The underlying technique is based upon the Ripple Down Rules (RDR) technology. RDR is a knowledge acquisition technology that allows the expert to interact directly with the system and construct knowledge incrementally on a case by case basis. RDR and its variants have been successfully applied to a wide range of problem types. However, there has been no research that has explored the adaptation of RDR to complex real-time, multi-agent environments. The domain chosen to develop our system was the Robocup 2D soccer simulation domain. We investigated an SCRDR approach to the problem and from this developed a more complex system based on generalised RDR. This system supported the incremental modelling of intermediate features during the knowledge acquisition process, allowing the experts to create their own abstractions of the domain. The system was extensively evaluated over a period of 6 months, to evaluate the level of performance of the multi-agent teams created by the system and to gather feedback about the usability of the system. During this period of time the system was successfully used by four soccer coaches with differing levels of soccer and computer expertise. All coaches were able to use the system to develop teams that could play at a world class level against the finalists from the Robocup 2007 2D simulation tournament. The approach we present is general enough to be applied to any complex planning problem, with the requirement that a rich feature language is developed to support the specific domain. Our studies confirm that although GRDR seems to be a useful framework for allowing experts to create their own layers of abstractions, in complex domains, some abstractions need to be expressed in low level code below the knowledge level. Our evaluation also suggests that the GRDR system could be improved via further integration with tools to restructure the KB for complex domains where expertise may be experimental and a more radical reorganisation of the KB is required.
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Hotz, Kenneth Joseph. "A visual and interactive environment for knowledge acquisition." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq23610.pdf.
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Stephens, Robert Andrew. "Representation and knowledge acquisition : the problem of language." Thesis, University of the West of England, Bristol, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321831.
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Thorpe, Patrick J. "Knowledge acquisition for expert systems in fibre production." Thesis, Loughborough University, 1992. https://dspace.lboro.ac.uk/2134/13749.
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The aim of the study described in this thesis is to investigate the application of expert system technology to acrylic fibre production, with a particular emphasis on knowledge acquisition requirements. In doing so, it is intended to provide an understanding of the requirements and appropriate techniques for the effective application of expert systems in the process industries; The scope of the study is limited to process fault administration which involves detecting, diagnosing arid correcting abnormalities in process operation. A methodology is provided for the systematic development of expert systems within the defined area of application. An important phase in the development methodology is that of expert system specification. This involves an analysis of expert behaviour and the specification of expert system functionality: In order to assist system specification, generic knowledge types and human expert activities have been identified within the context of process fault administration. Knowledge acquisition is discussed in terms of the requirements during each phase of the proposed development methodology. A detailed review is given of the available techniques for knowledge acquisition and an assessment is presented of the most appropriate techniques to apply during each phase of the methodology. A new knowledge acquisition technique is described. The technique is designed to record knowledge of process operation and process fault diagnosis. It is based on a hierarchical decomposition of the process in terms of process objectives. Two complementary forms of knowledge representation are produced: a hierarchy diagram which shows the dependency relationships between individual process objectives and a task statement table which provides a more. detailed explanation of the objectives. Finally, three. case studies are described in which the techniques described in the thesis were applied and developed.
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Patel, Jitendra M. "Automatic acquisition of knowledge for solving analysis tasks." Thesis, Open University, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.329567.
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Trice, Andrew W. "Facilitating consensus knowledge acquisition by Andrew W. Trice." Thesis, Massachusetts Institute of Technology, 1990. http://hdl.handle.net/1721.1/14086.
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Karunananda, Asoka S. "Investigating the use of metaphors for knowledge acquisition." Thesis, Keele University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262379.
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A major phase in the construction of Knowledge-Based Systems (KBSs) is the Knowledge Acquisition stage. It involves acquiring knowledge from experts, books, examples and from other relevant sources. Until recently, researchers assumed a simplistic view of knowledge which required it being 'extracted' or 'mined' from experts. It is now clear that this simplistic view ignored the rich epistemological, cognitive and perceptual basis of what we refer to as knowledge. This thesis set about to address this problem. It identifies domain analysis as an early stage in the knowledge acquisition process and argues that it should capture the expert's perception of the domain, rather than the knowledge engineer's view of the expert's perception. It puts forward the thesis that metaphors are invaluable cognitive devices for perceiving and articulating domains. This idea has been postulated by several other researchers but never, until now, tested. This thesis prescribes a novel method for exploiting metaphors for knowledge acquisition. The method is based on Black's interaction view of metaphors which has been merged with Kelly's personal construct psychology. We have implemented a tool, DAKUM, based on this new method and evaluated the usefulness of metaphors for knowledge acquisition. We conclude that metaphors are useful for constructing a domain's functions and structure. However, we note that metaphors are only useful, when describing Juzzy domains; their use in describing relatively organised domains could often lead to confusion. Metaphorically speaking, we conclude that using metaphors is analogous to using a walking stick. The latter is only useful when it is needed; otherwise its use is often a hindrance.
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Clark, Stephen. "Class-based statistical models for lexical knowledge acquisition." Thesis, University of Sussex, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341541.
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This thesis is about the automatic acquisition of a particular kind of lexical knowledge, namely the knowledge of which noun senses can fill the argument slots of predicates. The knowledge is represented using probabilities, which agrees with the intuition that there are no absolute constraints on the arguments of predicates, but that the constraints are satisfied to a certain degree; thus the problem of knowledge acquisition becomes the problem of probability estimation from corpus data. The problem with defining a probability model in terms of senses is that this involves a huge number of parameters, which results in a sparse data problem. The proposal here is to define a probability model over senses in a semantic hierarchy, and exploit the fact that senses can be grouped into classes consisting of semantically similar senses. A novel class-based estimation technique is developed, together with a procedure that determines a suitable class for a sense (given a predicate and argument position). The problem of determining a suitable class can be thought of as finding a suitable level of generalisation in the hierarchy. The generalisation procedure uses a statistical test to locate areas consisting of semantically similar senses, and, as well as being used for probability estimation, is also employed as part of a re-estimation algorithm for estimating sense frequencies from incomplete data. The rest of the thesis considers how the lexical knowledge can be used to resolve structural ambiguities, and provides empirical evaluations. The estimation techniques are first integrated into a parse selection system, using a probabilistic dependency model to rank the alternative parses for a sentence. Then, a PP-attachment task is used to provide an evaluation which is more focussed on the class-based estimation technique, and, finally, a pseudo disambiguation task is used to compare the estimation technique with alternative approaches.