Search (32 results, page 1 of 2)

  • × language_ss:"e"
  • × theme_ss:"Computerlinguistik"
  • × type_ss:"a"
  1. Ruge, G.: ¬A spreading activation network for automatic generation of thesaurus relationships (1991) 0.21
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    Date
    8.10.2000 11:52:22
    Source
    Library science with a slant to documentation. 28(1991) no.4, S.125-130
  2. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.10
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    Content
    Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
    Date
    8. 1.2013 10:22:32
  3. Porter, M.F.: ¬An algorithm for suffix stripping (1980) 0.07
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    Source
    Program. 14(1980), S.130-137
  4. Fox, C.: Lexical analysis and stoplists (1992) 0.05
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    Pages
    S.102-130
  5. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.04
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  6. Levin, M.; Krawczyk, S.; Bethard, S.; Jurafsky, D.: Citation-based bootstrapping for large-scale author disambiguation (2012) 0.03
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    Abstract
    We present a new, two-stage, self-supervised algorithm for author disambiguation in large bibliographic databases. In the first "bootstrap" stage, a collection of high-precision features is used to bootstrap a training set with positive and negative examples of coreferring authors. A supervised feature-based classifier is then trained on the bootstrap clusters and used to cluster the authors in a larger unlabeled dataset. Our self-supervised approach shares the advantages of unsupervised approaches (no need for expensive hand labels) as well as supervised approaches (a rich set of features that can be discriminatively trained). The algorithm disambiguates 54,000,000 author instances in Thomson Reuters' Web of Knowledge with B3 F1 of.807. We analyze parameters and features, particularly those from citation networks, which have not been deeply investigated in author disambiguation. The most important citation feature is self-citation, which can be approximated without expensive extraction of the full network. For the supervised stage, the minor improvement due to other citation features (increasing F1 from.748 to.767) suggests they may not be worth the trouble of extracting from databases that don't already have them. A lean feature set without expensive abstract and title features performs 130 times faster with about equal F1.
  7. Warner, A.J.: Natural language processing (1987) 0.03
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    Source
    Annual review of information science and technology. 22(1987), S.79-108
  8. McMahon, J.G.; Smith, F.J.: Improved statistical language model performance with automatic generated word hierarchies (1996) 0.02
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    Source
    Computational linguistics. 22(1996) no.2, S.217-248
  9. Somers, H.: Example-based machine translation : Review article (1999) 0.02
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    Date
    31. 7.1996 9:22:19
  10. Baayen, R.H.; Lieber, H.: Word frequency distributions and lexical semantics (1997) 0.02
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    Date
    28. 2.1999 10:48:22
  11. 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) 0.02
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    Date
    15. 3.2000 10:22:37
  12. Hutchins, J.: From first conception to first demonstration : the nascent years of machine translation, 1947-1954. A chronology (1997) 0.02
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    Date
    31. 7.1996 9:22:19
  13. Wanner, L.: Lexical choice in text generation and machine translation (1996) 0.01
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    Date
    31. 7.1996 9:22:19
  14. Riloff, E.: ¬An empirical study of automated dictionary construction for information extraction in three domains (1996) 0.01
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    Date
    6. 3.1997 16:22:15
  15. Basili, R.; Pazienza, M.T.; Velardi, P.: ¬An empirical symbolic approach to natural language processing (1996) 0.01
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    Date
    6. 3.1997 16:22:15
  16. Haas, S.W.: Natural language processing : toward large-scale, robust systems (1996) 0.01
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    Abstract
    State of the art review of natural language processing updating an earlier review published in ARIST 22(1987). Discusses important developments that have allowed for significant advances in the field of natural language processing: materials and resources; knowledge based systems and statistical approaches; and a strong emphasis on evaluation. Reviews some natural language processing applications and common problems still awaiting solution. Considers closely related applications such as language generation and th egeneration phase of machine translation which face the same problems as natural language processing. Covers natural language methodologies for information retrieval only briefly
  17. Morris, V.: Automated language identification of bibliographic resources (2020) 0.01
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    Date
    2. 3.2020 19:04:22
  18. Doszkocs, T.E.; Zamora, A.: Dictionary services and spelling aids for Web searching (2004) 0.01
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    Date
    14. 8.2004 17:22:56
    Source
    Online. 28(2004) no.3, S.22-29
  19. Schwarz, C.: THESYS: Thesaurus Syntax System : a fully automatic thesaurus building aid (1988) 0.01
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    Date
    6. 1.1999 10:22:07
  20. Kay, M.: ¬The proper place of men and machines in language translation (1997) 0.01
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    Date
    31. 7.1996 9:22:19