Search (11 results, page 1 of 1)

  • × year_i:[1990 TO 2000}
  • × theme_ss:"Wissensrepräsentation"
  1. Hodgson, J.P.E.: Knowledge representation and language in AI (1991) 0.00
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    Abstract
    The aim of this book is to highlight the relationship between knowledge representation and language in artificial intelligence, and in particular on the way in which the choice of representation influences the language used to discuss a problem - and vice versa. Opening with a discussion of knowledge representation methods, and following this with a look at reasoning methods, the author begins to make his case for the intimate relationship between language and representation. He shows how each representation method fits particularly well with some reasoning methods and less so with others, using specific languages as examples. The question of representation change, an important and complex issue about which very little is known, is addressed. Dr Hodgson gathers together recent work on problem solving, showing how, in some cases, it has been possible to use representation changes to recast problems into a language that makes them easier to solve. The author maintains throughout that the relationships that this book explores lie at the heart of the construction of large systems, examining a number of the current large AI systems from the viewpoint of representation and language to prove his point.
  2. Nagao, M.: Knowledge and inference (1990) 0.00
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    Abstract
    Knowledge and Inference discusses an important problem for software systems: How do we treat knowledge and ideas on a computer and how do we use inference to solve problems on a computer? The book talks about the problems of knowledge and inference for the purpose of merging artificial intelligence and library science. The book begins by clarifying the concept of ""knowledge"" from many points of view, followed by a chapter on the current state of library science and the place of artificial intelligence in library science. Subsequent chapters cover central topics in the artificial intelligence: search and problem solving, methods of making proofs, and the use of knowledge in looking for a proof. There is also a discussion of how to use the knowledge system. The final chapter describes a popular expert system. It describes tools for building expert systems using an example based on Expert Systems-A Practical Introduction by P. Sell (Macmillian, 1985). This type of software is called an ""expert system shell."" This book was written as a textbook for undergraduate students covering only the basics but explaining as much detail as possible.
  3. Roth, G.; Schwegler, H.: Kognitive Referenz und Selbstreferentialität des Gehirns : ein Beitrag zur Klärung des Verhältnisses zwischen Erkenntnistheorie und Hirnforschung (1992) 0.00
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    Date
    20.12.2018 12:39:29
  4. Schmitz-Esser, W.: Language of general communication and concept compatibility (1996) 0.00
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    Pages
    S.11-22
  5. Giunchiglia, F.; Villafiorita, A.; Walsh, T.: Theories of abstraction (1997) 0.00
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    Date
    1.10.2018 14:13:22
  6. Rindflesch, T.C.; Aronson, A.R.: Semantic processing in information retrieval (1993) 0.00
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    Date
    29. 6.2015 14:51:28
  7. Priss, U.: Faceted knowledge representation (1999) 0.00
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    Date
    22. 1.2016 17:30:31
  8. Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996) 0.00
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    Source
    Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al
  9. Priss, U.: Description logic and faceted knowledge representation (1999) 0.00
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    Date
    22. 1.2016 17:30:31
  10. Noy, N.F.: Knowledge representation for intelligent information retrieval in experimental sciences (1997) 0.00
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    Abstract
    More and more information is available on-line every day. The greater the amount of on-line information, the greater the demand for tools that process and disseminate this information. Processing electronic information in the form of text and answering users' queries about that information intelligently is one of the great challenges in natural language processing and information retrieval. The research presented in this talk is centered on the latter of these two tasks: intelligent information retrieval. In order for information to be retrieved, it first needs to be formalized in a database or knowledge base. The ontology for this formalization and assumptions it is based on are crucial to successful intelligent information retrieval. We have concentrated our effort on developing an ontology for representing knowledge in the domains of experimental sciences, molecular biology in particular. We show that existing ontological models cannot be readily applied to represent this domain adequately. For example, the fundamental notion of ontology design that every "real" object is defined as an instance of a category seems incompatible with the universe where objects can change their category as a result of experimental procedures. Another important problem is representing complex structures such as DNA, mixtures, populations of molecules, etc., that are very common in molecular biology. We present extensions that need to be made to an ontology to cover these issues: the representation of transformations that change the structure and/or category of their participants, and the component relations and spatial structures of complex objects. We demonstrate examples of how the proposed representations can be used to improve the quality and completeness of answers to user queries; discuss techniques for evaluating ontologies and show a prototype of an Information Retrieval System that we developed.
  11. Soergel, D.: SemWeb: Proposal for an Open, multifunctional, multilingual system for integrated access to knowledge about concepts and terminology : exploration and development of the concept (1996) 0.00
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    Date
    15. 6.2010 19:25:29