Search (47 results, page 1 of 3)

  • × language_ss:"e"
  • × theme_ss:"Computerlinguistik"
  1. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.43
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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
  2. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.34
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  3. Huo, W.: Automatic multi-word term extraction and its application to Web-page summarization (2012) 0.31
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    Content
    A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science in Computer Science. Vgl. Unter: http://www.inf.ufrgs.br%2F~ceramisch%2Fdownload_files%2Fpublications%2F2009%2Fp01.pdf.
    Date
    10. 1.2013 19:22:47
  4. 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) 0.10
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    Date
    15. 3.2000 10:22:37
    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  5. Sharada, B.A.: Identification and interpretation of metaphors in document titles (1999) 0.03
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  6. Vossen, P.; Bloksma, L.; Alonge, A.; Marinai, E.; Peters, C.; Catellon, I.; Marti, M.A.; Rigau, G.: Compatibility in interpretation of relations in EuroWordNet (1998) 0.02
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  7. Varma, V.; Reddy, A.S.: Knowledge based metaphor interpretation (1996) 0.02
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  8. Rindflesch, T.C.; Fizsman, M.: The interaction of domain knowledge and linguistic structure in natural language processing : interpreting hypernymic propositions in biomedical text (2003) 0.02
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    Abstract
    Interpretation of semantic propositions in free-text documents such as MEDLINE citations would provide valuable support for biomedical applications, and several approaches to semantic interpretation are being pursued in the biomedical informatics community. In this paper, we describe a methodology for interpreting linguistic structures that encode hypernymic propositions, in which a more specific concept is in a taxonomic relationship with a more general concept. In order to effectively process these constructions, we exploit underspecified syntactic analysis and structured domain knowledge from the Unified Medical Language System (UMLS). After introducing the syntactic processing on which our system depends, we focus on the UMLS knowledge that supports interpretation of hypernymic propositions. We first use semantic groups from the Semantic Network to ensure that the two concepts involved are compatible; hierarchical information in the Metathesaurus then determines which concept is more general and which more specific. A preliminary evaluation of a sample based on the semantic group Chemicals and Drugs provides 83% precision. An error analysis was conducted and potential solutions to the problems encountered are presented. The research discussed here serves as a paradigm for investigating the interaction between domain knowledge and linguistic structure in natural language processing, and could also make a contribution to research on automatic processing of discourse structure. Additional implications of the system we present include its integration in advanced semantic interpretation processors for biomedical text and its use for information extraction in specific domains. The approach has the potential to support a range of applications, including information retrieval and ontology engineering.
  9. Schneider, J.W.; Borlund, P.: ¬A bibliometric-based semiautomatic approach to identification of candidate thesaurus terms : parsing and filtering of noun phrases from citation contexts (2005) 0.01
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    Date
    8. 3.2007 19:55:22
    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  10. Bacchin, M.; Ferro, N.; Melucci, M.: ¬A probabilistic model for stemmer generation (2005) 0.01
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    Abstract
    In this paper we will present a language-independent probabilistic model which can automatically generate stemmers. Stemmers can improve the retrieval effectiveness of information retrieval systems, however the designing and the implementation of stemmers requires a laborious amount of effort due to the fact that documents and queries are often written or spoken in several different languages. The probabilistic model proposed in this paper aims at the development of stemmers used for several languages. The proposed model describes the mutual reinforcement relationship between stems and derivations and then provides a probabilistic interpretation. A series of experiments shows that the stemmers generated by the probabilistic model are as effective as the ones based on linguistic knowledge.
  11. Rayson, P.; Piao, S.; Sharoff, S.; Evert, S.; Moiron, B.V.: Multiword expressions : hard going or plain sailing? (2015) 0.01
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    Abstract
    Over the past two decades or so, Multi-Word Expressions (MWEs; also called Multi-word Units) have been an increasingly important concern for Computational Linguistics and Natural Language Processing (NLP). The term MWE has been used to refer to various types of linguistic units and expressions, including idioms, noun compounds, phrasal verbs, light verbs and other habitual collocations. However, while there is no universally agreed definition for MWE as yet, most researchers use the term to refer to those frequently occurring phrasal units which are subject to certain level of semantic opaqueness, or non-compositionality. Non-compositional MWEs pose tough challenges for automatic analysis because their interpretation cannot be achieved by directly combining the semantics of their constituents, thereby causing the "pain in the neck of NLP".
  12. Al-Khatib, K.; Ghosa, T.; Hou, Y.; Waard, A. de; Freitag, D.: Argument mining for scholarly document processing : taking stock and looking ahead (2021) 0.01
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    Abstract
    Argument mining targets structures in natural language related to interpretation and persuasion. Most scholarly discourse involves interpreting experimental evidence and attempting to persuade other scientists to adopt the same conclusions, which could benefit from argument mining techniques. However, While various argument mining studies have addressed student essays and news articles, those that target scientific discourse are still scarce. This paper surveys existing work in argument mining of scholarly discourse, and provides an overview of current models, data, tasks, and applications. We identify a number of key challenges confronting argument mining in the scientific domain, and suggest some possible solutions and future directions.
  13. Niemi, T.; Jämsen, J.: ¬A query language for discovering semantic associations, part II : sample queries and query evaluation (2007) 0.01
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    Abstract
    In our query language introduced in Part I (Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1559-1568) the user can formulate queries to find out (possibly complex) semantic relationships among entities. In this article we demonstrate the usage of our query language and discuss the new applications that it supports. We categorize several query types and give sample queries. The query types are categorized based on whether the entities specified in a query are known or unknown to the user in advance, and whether text information in documents is utilized. Natural language is used to represent the results of queries in order to facilitate correct interpretation by the user. We discuss briefly the issues related to the prototype implementation of the query language and show that an independent operation like Rho (Sheth et al., 2005; Anyanwu & Sheth, 2002, 2003), which presupposes entities of interest to be known in advance, is exceedingly inefficient in emulating the behavior of our query language. The discussion also covers potential problems, and challenges for future work.
  14. Warner, A.J.: Natural language processing (1987) 0.01
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    Source
    Annual review of information science and technology. 22(1987), S.79-108
  15. McMahon, J.G.; Smith, F.J.: Improved statistical language model performance with automatic generated word hierarchies (1996) 0.01
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    Computational linguistics. 22(1996) no.2, S.217-248
  16. Ruge, G.: ¬A spreading activation network for automatic generation of thesaurus relationships (1991) 0.01
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    Date
    8.10.2000 11:52:22
  17. Somers, H.: Example-based machine translation : Review article (1999) 0.01
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  18. New tools for human translators (1997) 0.01
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  19. Baayen, R.H.; Lieber, H.: Word frequency distributions and lexical semantics (1997) 0.01
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  20. Boleda, G.; Evert, S.: Multiword expressions : a pain in the neck of lexical semantics (2009) 0.00
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    Date
    1. 3.2013 14:56:22

Years

Languages

Types

  • a 39
  • m 3
  • s 3
  • p 2
  • el 1
  • x 1
  • More… Less…