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Knowledge representation and reasoning

About: Knowledge representation and reasoning is a research topic. Over the lifetime, 20078 publications have been published within this topic receiving 446310 citations. The topic is also known as: KR & KR².


Papers
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Journal ArticleDOI
TL;DR: Methods from George Kelly's personal construct psychology have been incorporated into a computer program, the Expertise Transfer System, which interviews experts, and helps them construct, analyse, test and refine knowledge bases.
Abstract: Retrieving problem-solving information from a human expert is a major problem when building an expert system. Methods from George Kelly's personal construct psychology have been incorporated into a computer program, the Expertise Transfer System, which interviews experts, and helps them construct, analyse, test and refine knowledge bases. Conflicts in the problem-solving methods of the expert may be enumerated and explored, and knowledge bases from several experts may be combined into one consultation system. Fast (one to two hour) expert system prototyping is possible with the use of the system, and knowledge bases may be constructed for various expert system tools.

209 citations

Book ChapterDOI
23 Sep 2002
TL;DR: This paper presents a probabilistic extension of SHOQ(D), called P-SHOQ (D), to allow for dealing with Probabilistic ontologies in the semantic web, and presents sound and complete reasoning techniques that show in particular that reasoning in P- SHOZ(D) is decidable.
Abstract: Ontologies play a central role in the development of the semantic web, as they provide precise definitions of shared terms in web resources. One important web ontology language is DAML+OIL; it has a formal semantics and a reasoning support through a mapping to the expressive description logic SHOQ(D) with the addition of inverse roles. In this paper, we present a probabilistic extension of SHOQ(D), called P-SHOQ(D), to allow for dealing with probabilistic ontologies in the semantic web. The description logic P-SHOQ(D) is based on the notion of probabilistic lexicographic entailment from probabilistic default reasoning. It allows to express rich probabilistic knowledge about concepts and instances, as well as default knowledge about concepts. We also present sound and complete reasoning techniques for P-SHOQ(D), which are based on reductions to classical reasoning in SHOQ(D) and to linear programming, and which show in particular that reasoning in P-SHOQ(D) is decidable.

208 citations

Book ChapterDOI
TL;DR: The state of the art in Qualitative Spatial Reasoning is surveyed, covering representation and reasoning issues as well as pointing to some application areas.
Abstract: The field of Qualitative Spatial Reasoning is now an active research area in its own right within AI (and also in Geographical Information Systems) having grown out of earlier work in philosophical logic and more general Qualitative Reasoning in AI. In this paper (which is an updated version of [25]) I will survey the state of the art in Qualitative Spatial Reasoning, covering representation and reasoning issues as well as pointing to some application areas.

208 citations

Journal ArticleDOI
TL;DR: The spatial query and spatial reasoning based on a 2D C-string representation are presented and the similarity measure is defined and the algorithm for similarity retrieval of iconic images is also proposed.

207 citations

Journal ArticleDOI
TL;DR: This work has developed methods for mapping web sources into a uniform representation that makes it simple and efficient to integrate multiple sources and makes it easy to maintain these agents and incorporate new sources as they become available.
Abstract: The Web is based on a browsing paradigm that makes it difficult to retrieve and integrate data from multiple sites. Today, the only way to do this is to build specialized applications, which are time-consuming to develop and difficult to maintain. We have addressed this problem by creating the technology and tools for rapidly constructing information agents that extract, query, and integrate data from web sources. Our approach is based on a uniform representation that makes it simple and efficient to integrate multiple sources. Instead of building specialized algorithms for handling web sources, we have developed methods for mapping web sources into this uniform representation. This approach builds on work from knowledge representation, databases, machine learning and automated planning. The resulting system, called Ariadne, makes it fast and easy to build new information agents that access existing web sources. Ariadne also makes it easy to maintain these agents and incorporate new sources as they become available.

207 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202378
2022192
2021390
2020528
2019566
2018509