Number of found records: 23
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NEWBY, Gregory B. |
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The necessity for information space mapping for information retrieval on the semantic web. |
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Information Research, 2002, Vol. 7 No. 4. |
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On line ( 15/06/2004) |
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The Semantic Web offers exciting possibilities for information retrieval (IR). In IR, we would like systems that go beyond simply matching words in documents and queries, and instead match based on topic, data type, relations among data, and many other qualities. The Semantic Web, through fuzzy matching of information spaces from different sources, will provide for much more specific information seeking than current Web-based search engines or other IR systems. In order to succeed, however, it is necessary to map between the differing schema, metadata standards, namespaces and so forth used by documents on the Semantic Web. This information space mapping may be accomplished by a simple match or table lookup when document sets come from similar or otherwise well-defined domains. When the match is less precise, sets of rules or algorithms may be employed to map between information spaces. When schema or metadata are inconsistent, though, we are left with a similar data environment as the modern Web, and must rely on the context of the documents themselves to determine the mapping between information spaces. (AU) |
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information retrieval; semantic network; semantic web; mapping |
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POLANCO, X.; FRANCOIS, C.; KEIM J.P. |
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Artificial neural network technology for the classification and cartography of scientific and technical information. |
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Scientometrics, 1998, vol.41, n.1-2, pp.69-82 |
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On line (09/05/2005) |
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Paper presented at the 6th conference of the International Society for Scientometrics and Informetrics, Jerusalem, Israel, 16-19 June 1997. Describes the implementation of multivariate data analysis: NEURODOC applies the axial k-means method for automatic, non hierarchical cluster analysis and a Principal Component Analysis for representing the clusters on a map. Introduces Artificial Neural Networks (ANNs) to extend NEURODOC into a neural platform for the cluster analysis and cartography of bibliographic data. The ANNs tested are: the Adaptive Resonance Theory; a Multilayer Perceptron; and an associative network with unsupervised learning (KOHONEN). This platform is intended for quantitative analysis of information. (AU) |
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Scientometrics-; Citations-; Mapping-; Cluster Analysis; Artificial-neural-networks |
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SIMONS, Patrik; NIEMELÄ, Ilkka; SOININEN, Timo |
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Extending and implementing the stable model semantics |
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Artificial-Intelligence. Jun. 2002, vol. 138, nº 1-2, pp.181-234. il. refs. PY: 2002 |
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On line (09/05/2005) |
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A novel logic program like language, weight constraint rules, is developed for answer set programming purposes. It generalizes normal logic programs by allowing weight constraints in place of literals to represent, e.g., cardinality and resource constraints and by providing optimization capabilities. A declarative semantics is developed which extends the stable model semantics of normal programs. The computational complexity of the language is shown to be similar to that of normal programs under the stable model semantics. A simple embedding of general weight constraint rules to a small subclass of the language called basic constraint rules is devised. An implementation of the language, the system, is developed based on this embedding. It uses a two level architecture consisting of a front-end and a kernel language implementation. The front-end allows restricted use of variables and functions and compiles general weight constraint rules to basic constraint rules. A major part of the work is the development of an efficient search procedure for computing stable models for this kernel language. The procedure is compared with and empirically tested against satisfiability checkers and an implementation of the stable model semantics. It offers a competitive implementation of the stable model semantics for normal programs and attractive performance for problems where the new types of rules provide a compact representation. (AU) |
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Logic programs; semantics; |
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SOWA, John F. |
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Site Directory, 1984-2000. |
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On line ( 15/06/2004) |
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This web site contains a collection of directories. 1:Conceptual Graphs are a system of knowledge representation based on the semantic networks of AI and the logic of Charles Sanders Peirce. This directory contains the draft proposed ANSI standard for CGs, some examples and tutorials about CGs, a bibliography of books about CGs, and links to web sites with CG tools and resources. 2: The book Knowledge Representation by John F. Sowa has recently been published. This directory contains some information about the book, including on-line copies of the preface and the table of contents. The on-line index contains over 600 links to web sites that contain background readings about the people and topics mentioned in the book. 3: Ontology is the study of existence. An ontology is a system of categories for classifying and talking about the things that are assumed to exist. This directory contains a summary of the ontology developed and used in the KR book by John Sowa. 4: Computer systems of the twenty-first century will be based on the principles of computer science that were established during the nineteenth and twentieth centuries. This directory contains memoirs, observations, and predictions about computer history. At the moment, it contains only one web page, which discusses the law of standards. 5: Any system of classification inevitably has miscellaneous stuff that doesn't quite fit in the other categories. This directory contains some of that stuff, including a tutorial on the mathematical background that is used, mentioned, or referenced in the other web pages. (Web) |
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computer systems; ontology; knowledge representation; concept maps; semantic networks |
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