Search (29 results, page 1 of 2)

  • × language_ss:"e"
  • × theme_ss:"Computerlinguistik"
  • × year_i:[1990 TO 2000}
  1. Dorr, B.J.: Large-scale dictionary construction for foreign language tutoring and interlingual machine translation (1997) 0.01
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    Abstract
    Describes techniques for automatic construction of dictionaries for use in large-scale foreign language tutoring (FLT) and interlingual machine translation (MT) systems. The dictionaries are based on a language independent representation called lexical conceptual structure (LCS). Demonstrates that synonymous verb senses share distribution patterns. Shows how the syntax-semantics relation can be used to develop a lexical acquisition approach that contributes both toward the enrichment of existing online resources and toward the development of lexicons containing more complete information than is provided in any of these resources alone. Describes the structure of the LCS and shows how this representation is used in FLT and MT. Focuses on the problem of building LCS dictionaries for large-scale FLT and MT. Describes authoring tools for manual and semi-automatic construction of LCS dictionaries. Presents an approach that uses linguistic techniques for building word definitions automatically. The techniques have been implemented as part of a set of lixicon-development tools used in the MILT FLT project
    Date
    31. 7.1996 9:22:19
  2. Melby, A.: Some notes on 'The proper place of men and machines in language translation' (1997) 0.00
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    Date
    31. 7.1996 9:22:19
    Source
    Machine translation. 12(1997) nos.1/2, S.29-34
  3. Proszeky, G.: Language technology tools in the translator's practice (1999) 0.00
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    Date
    30. 3.2002 18:29:40
  4. McMahon, J.G.; Smith, F.J.: Improved statistical language model performance with automatic generated word hierarchies (1996) 0.00
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    Source
    Computational linguistics. 22(1996) no.2, S.217-248
  5. Ruge, G.: ¬A spreading activation network for automatic generation of thesaurus relationships (1991) 0.00
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    Date
    8.10.2000 11:52:22
  6. Somers, H.: Example-based machine translation : Review article (1999) 0.00
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    Date
    31. 7.1996 9:22:19
  7. New tools for human translators (1997) 0.00
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    Date
    31. 7.1996 9:22:19
  8. Baayen, R.H.; Lieber, H.: Word frequency distributions and lexical semantics (1997) 0.00
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    Date
    28. 2.1999 10:48:22
  9. Rahmstorf, G.: Information retrieval using conceptual representations of phrases (1994) 0.00
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    Abstract
    The information retrieval problem is described starting from an analysis of the concepts 'user's information request' and 'information offerings of texts'. It is shown that natural language phrases are a more adequate medium for expressing information requests and information offerings than character string based query and indexing languages complemented by Boolean oprators. The phrases must be represented as concepts to reach a language invariant level for rule based relevance analysis. The special type of representation called advanced thesaurus is used for the semantic representation of natural language phrases and for relevance processing. The analysis of the retrieval problem leads to a symmetric system structure
  10. Byrne, C.C.; McCracken, S.A.: ¬An adaptive thesaurus employing semantic distance, relational inheritance and nominal compound interpretation for linguistic support of information retrieval (1999) 0.00
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    Date
    15. 3.2000 10:22:37
  11. Stede, M.: Lexicalization in natural language generation : a survey (1994/95) 0.00
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    Abstract
    In natural language generation, a meaning representation of some kind is successively transformed into a sentence or a text. Naturally, a central subtask of this problem is the choice of words, or lexicalization. Proposes 4 major issues that determine how a generator tackles lexicalization, and surveys the contributions that research have made to them. Identifies open problems, and sketches a possible direction for research
  12. 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.
  13. Czejdo. B.D.; Tucci, R.P.: ¬A dataflow graphical language for database applications (1994) 0.00
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    Date
    20.10.2000 13:29:46
  14. Whitelock, P.; Kilby, K.: Linguistic and computational techniques in machine translation system design : 2nd ed (1995) 0.00
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    Date
    29. 3.1996 18:28:09
  15. Hutchins, J.: From first conception to first demonstration : the nascent years of machine translation, 1947-1954. A chronology (1997) 0.00
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    Date
    31. 7.1996 9:22:19
  16. Sebastiani, F.: ¬A tutorial an automated text categorisation (1999) 0.00
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    Abstract
    The automated categorisation (or classification) of texts into topical categories has a long history, dating back at least to 1960. Until the late '80s, the dominant approach to the problem involved knowledge-engineering automatic categorisers, i.e. manually building a set of rules encoding expert knowledge an how to classify documents. In the '90s, with the booming production and availability of on-line documents, automated text categorisation has witnessed an increased and renewed interest. A newer paradigm based an machine learning has superseded the previous approach. Within this paradigm, a general inductive process automatically builds a classifier by "learning", from a set of previously classified documents, the characteristics of one or more categories; the advantages are a very good effectiveness, a considerable savings in terms of expert manpower, and domain independence. In this tutorial we look at the main approaches that have been taken towards automatic text categorisation within the general machine learning paradigm. Issues of document indexing, classifier construction, and classifier evaluation, will be touched upon.
  17. Chiba, K.; Kyojima, M.: Document transformation based on syntax-directed free translation (1995) 0.00
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    Source
    Electronic publishing. 8(1995) no.1, S.15-29
  18. Wanner, L.: Lexical choice in text generation and machine translation (1996) 0.00
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    Date
    31. 7.1996 9:22:19
  19. Riloff, E.: ¬An empirical study of automated dictionary construction for information extraction in three domains (1996) 0.00
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    Date
    6. 3.1997 16:22:15
  20. Basili, R.; Pazienza, M.T.; Velardi, P.: ¬An empirical symbolic approach to natural language processing (1996) 0.00
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    Date
    6. 3.1997 16:22:15