Number of found records: 11
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MARCU, Daniel |
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Daniel Marcu’s Homepage |
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University of Southern California, 1998 |
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On line ( 15/06/2004) |
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Web site of Prof. Daniel Marcu, Information Sciences Institute of Southern California University, expert on computational linguistics and knowledge representation |
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computational linguistics; knowledge representation; natural language processing; summarization |
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PETERS, Stanley |
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Computational Semantics Laboratory |
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Stanford: Computational Semantics Laboratory, 1999. |
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On line ( 15/06/2004) |
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We are a research group at the Center for the Study of Language and We are a research group at the Center for the Study of Language and Information (CSLI) at Stanford University, under the direction of Stanley Peters. We work on a number of projects which involve semantics -- the study of meaning -- at the intersection of linguistics and computer science. A unifying theme in our research is an emphasis on the role of context in determining meaning. We are particularly interested in theoretical models of communication, language, dialogue, computation, and inference which take into account the context in which these activities are occurring. We are also interested in applying research results to practical applications and real-world problems. Current or recent projects have been in the areas of information retrieval, natural language processing, dialogue systems, machine translation, programming languages, and cooperating software agents. (AU) |
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computational linguistics; computational semantics; natural language processing; information systems |
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RIJSBERGEN, C. J. van |
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Automatic text analysis |
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Information retrieval. Information Retrieval group. University of Glasgow, 1979 |
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PDF |
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The starting point of the text analysis process may be the complete document text, an abstract, the title only, or perhaps a list of words only. From it the process must produce a document representative in a form which the computer can handle. The chapter starts with the original ideas of Luhn on which much of automatic text analysis has been built, and then goes on to describe a concrete way of generating document representatives. Furthermore, ways of exploiting and improving document representatives through weighting or classifying keywords are discussed. In passing, some of the evidence for automatic indexing is presented. (AU) |
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Automatic text analysis; abstract; automatic indexing; knowledge representation |
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Universidad de Cambridge |
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Mit: Artificial Intelligence Laboratory |
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Cambridge, 2004 |
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On line ( 15/06/2004) |
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The Artificial Intelligence Laboratory has been an active entity at MIT in one form or another since at least 1959. Our goal is to understand the nature of intelligence and to engineer systems that exhibit intelligence. We are an interdisciplinary laboratory of over 200 people that spans several academic departments and has active projects ongoing with members of every academic school at MIT. Our intellectual goal is to understand how the human mind works. We believe that vision, robotics, and language are the keys to understanding intelligence, and as such our laboratory is much more heavily biased in these directions than many other Artificial Intelligence laboratories (Web) |
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artificial intelligence; information systems; robotics; computational systems |
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