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models, retrieval methods, result organization, etc. Table 1, extending van
Rijsbergen's comparison of the difference between data retrieval and information retrieval, summarizes the main characteristics of data retrieval, information retrieval, and knowledge retrieval. The core of data retrieval and
324:
From the retrieval perspective, knowledge retrieval systems focus on semantics and better organization of information. Data retrieval and information retrieval organize the data and documents by indexing, while knowledge retrieval organize information by indicating connections between elements in
292:
Knowledge retrieval focuses on the knowledge level. We need to examine how to extract, represent, and use the knowledge in data and information. Knowledge retrieval systems provide knowledge to users in a structured way. Compared to data retrieval and information retrieval, they use different
298:
information retrieval is retrieval subsystems. Data retrieval gets results through
Boolean match. Information retrieval uses partial match and best match. Knowledge retrieval is also based on partial match and best match.
96:
The goal of knowledge retrieval systems is to reduce the burden of those processes by improved search and representation. This improvement is needed to leverage the increasing data volumes available on the
Internet.
745:
758:
735:
Berners-Lee, T., Hall, W., Hendler, J.A., O’Hara, K., Shadbolt, N. and
Weitzner, D.J. A Framework for Web science, Foundations and Trends in Web Science, 2006, 1(1): 1-130.
341:
for knowledge reasoning and relevant strategies have been investigated, which may serve as possible logic reasoning foundations for text based knowledge retrieval.
157:
641:
Yiyu Yao, Yi Zeng, Ning Zhong, Xiangji Huang. Knowledge
Retrieval (KR). In: Proceedings of the 2007 IEEE/WIC/ACM International Conference on Web Intelligence,
204:
575:
465:
Topics listed under each entry serve as examples and do not form a complete list. And many related disciplines should be added as the field grows mature.
186:
348:
perspective, especially from cognitive psychology and cognitive neuroscience perspective, the neurobiological basis for knowledge retrieval in the
689:
Zeng, Y., Yao, Y.Y. and Zhong, N. Granular structurebased knowledge retrieval , Proceedings of the Joint
Conference of the Seventh Conference of
238:
552:
Yao, Y.Y. Information retrieval support systems, Proceedings of the 2002 IEEE International
Conference on Fuzzy Systems, 2002, 1092-1097.
774:, Mirella Dapretto. “I Know You Are But What Am I?!”: Neural Bases of Self-and Social Knowledge Retrieval in Children and Adults,
540:
337:
perspective, a logic framework concentrating on fuzziness of knowledge queries has been proposed and investigated in detail.
305:, and information retrieval uses inductive inference. Considering the limitations from the assumptions of different logics,
93:
Both approaches require a user to read and analyze often long lists of data sets or documents in order to extract meaning.
662:
797:
381:: cognitive psychology, cognitive neuroscience, cognitive informatics, concept formation and learning, decision making,
775:
454:
382:
254:
246:
458:
497:, Proceedings of the 1990 IEEE International Conference on Systems, Man and Cybernetics, 1990: 269-275.
72:
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and the idea of unifying reasoning and search may be effective methods of reasoning at the web scale.
450:
748:, Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence, 2004: 524-528.
613:
562:
372:
481:
436:
428:
105:
Data
Retrieval and Information Retrieval are earlier and more basic forms of information access.
723:
402:
56:
32:
642:
527:
78:
600:
392:
364:
Knowledge retrieval can draw results from the following related theories and technologies:
161:
28:
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543:, Proceedings of the 2nd annual ACM conference on Hypertext and Hypermedia, 1989: 147-158.
413:, deductive inference, associative reasoning, analogical reasoning, approximate reasoning.
8:
510:
424:
410:
177:
171:
153:
149:
144:
48:
494:
710:
Baeza-Yates, R. and
Ribeiro-Neto, B. Modern Information Retrieval, AddisonWesley, 1999.
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The knowledge retrieval matrix: codification and personification as separate strategies
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research, engineering and consulting company. VINE: The journal of information and
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44:
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Bellinger, G., Castro, D. and Mills, A. Data, Information, Knowledge, and Wisdom,
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as opposed to simple lists of data items. It draws on a range of fields including
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242:
233:
694:
659:
646:
270:
182:
791:
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Martin, P. and Eklund, P.W. Knowledge retrieval and the World Wide Web, IEEE
432:
82:
526:, Proceedings of the 7th International Symposium on Logic Formalizations of
24:
480:
Frisch, A.M. Knowledge
Retrieval as Specialized Inference, Ph.D. thesis,
391:: preprocessing, classification, clustering, prediction, postprocessing,
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310:
52:
574:
Robert Loew, Katrin Kuemmel, Judith Ruprecht, Udo Bleimann, Paul Walsh.
19:
seeks to return information in a structured form, consistent with human
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306:
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Stefania Mariano, Andrea Casey. The process of knowledge retrieval: A
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75:, are well suitable for the storage and retrieval of structured data.
40:
20:
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In the field of retrieval systems, established approaches include:
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100:
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van Rijsbergen, C.J. Information Retrieval, Butterworths, 1979.
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36:
85:, are very effective in finding the relevant documents or
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A logic framework of knowledge retrieval with fuzziness
616:, Journal of Knowledge Management, 9(4), 133-143, 2005.
761:. Behavioral and Brain Science, 22(2): 303-303, 1999.
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Analysis and organization of knowledge for retrieval
317:) cannot reason efficiently. Associative reasoning,
301:From an inference perspective, data retrieval uses
726:, IEEE Internet Computing, 2007, 11(2): 96, 94-95.
371:: knowledge acquisition, knowledge organization,
789:
701:, and the First Forum of Web Intelligence, 2007.
541:A visual representation for knowledge structures
576:Approaches for personalised knowledge retrieval
524:A framework for commonsense knowledge retrieval
565:and Knowledge Retrieval , Science Press, 2005.
101:Comparison with data and information retrieval
676:
674:
375:, knowledge validation, knowledge management.
660:http://www.systemsthinking.org/dikw/dikw.htm
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635:
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427:, information retrieval, database systems,
724:Unifying reasoning and search to web scale
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629:, ASLIB Proceedings, 22(12), 607-616,1970.
352:has been investigated, and may serve as a
329:Frameworks for knowledge retrieval systems
632:
713:
505:
503:
495:A graph based knowledge retrieval system
389:Machine learning and knowledge discovery
759:The neurobiology of knowledge retrieval
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561:Zhou, N., Zhang, Y.F. and Zhang, L.Y.
359:
500:
738:
405:, predicate logic, attribute logic,
221:knowledge unit, knowledge structure
649:, USA, November 2–5, 2007, 729-735.
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757:Tranel, Daniel, Damasio, Antonio.
14:
809:
776:Journal of Cognitive Neuroscience
612:Jens Gammelgaard, Thomas Ritter.
722:Fensel, D. and van Harmelen, F.
71:Data retrieval systems, such as
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455:natural language understanding
1:
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459:natural language processing
73:database management systems
62:
10:
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798:Knowledge-oriented systems
744:Chen, B.C. and Hsiang, J.
493:Kame, M. and Quintana, Y.
383:human–computer interaction
133:partial match, best match
563:Information Visualization
451:computational linguistics
356:for knowledge retrieval.
130:partial match, best match
522:Oertel, P. and Amir, E.
437:decision support systems
373:knowledge representation
286:a set of knowledge unit
482:University of Rochester
429:knowledge-based systems
27:(theory of knowledge),
431:, rule-based systems,
417:Information technology
57:information technology
33:cognitive neuroscience
770:Jennifer H. Pfeifer,
697:, the First Forum of
643:IEEE Computer Society
603:systems, 37(3), 2007.
528:Commonsense Reasoning
513:, 2000, 15(3): 18-25.
283:sections or documents
158:associative reasoning
116:Information Retrieval
81:systems, such as web
79:Information retrieval
772:Matthew D. Lieberman
601:knowledge management
393:statistical learning
319:analogical reasoning
267:document collections
162:analogical reasoning
119:Knowledge Retrieval
29:cognitive psychology
511:Intelligent Systems
425:information science
411:inductive inference
403:propositional logic
399:Logic and inference
369:Theory of knowledge
360:Related disciplines
303:deductive inference
207:, natural language
205:knowledge structure
196:artificial language
178:probabilistic model
172:deterministic model
154:inductive inference
150:deductive inference
145:inductive inference
141:deductive inference
49:knowledge discovery
21:cognitive processes
17:Knowledge retrieval
699:Granular Computing
665:2016-10-17 at the
625:J.E.L. Farradane.
421:information theory
232:natural language,
580:Internet Research
441:intelligent agent
379:Cognitive science
346:cognitive science
325:those documents.
315:first order logic
307:traditional logic
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277:Retrieved Results
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176:statistical and
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247:production rule
243:predicate logic
234:markup language
187:inference model
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113:Data Retrieval
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212:Organization
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25:epistemology
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447:Linguistics
443:technology.
350:human brain
53:linguistics
593:case study
469:References
313:subset of
780:MIT Press
778:, 19(8),
691:Rough Set
295:inference
249:, frame,
138:Inference
87:web pages
41:inference
792:Category
663:Archived
280:data set
264:database
255:ontology
63:Overview
530:, 2005.
484:, 1986.
395:theory.
261:Storage
55:, and
344:From
333:From
193:Query
168:Model
124:Match
37:logic
693:and
311:Horn
47:and
39:and
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89:.
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