Search (89 results, page 1 of 5)

  • × theme_ss:"Computerlinguistik"
  1. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.23 
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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) 0.14 
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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) 0.12 
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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. Godby, J.: WordSmith research project bridges gap between tokens and indexes (1998) 0.05 
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    Abstract
    Reports on an OCLC natural language processing research project to develop methods for identifying terminology in unstructured electronic text, especially material associated with new cultural trends and emerging subjects. Current OCLC production software can only identify single words as indexable terms in full text documents, thus a major goal of the WordSmith project is to develop software that can automatically identify and intelligently organize phrases for uses in database indexes. By analyzing user terminology from local newspapers in the USA, the latest cultural trends and technical developments as well as personal and geographic names have been drawm out. Notes that this new vocabulary can also be mapped into reference works
    Source
    OCLC newsletter. 1998, no.234, Jul/Aug, S.22-24
  5. Fóris, A.: Network theory and terminology (2013) 0.04 
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    Abstract
    The paper aims to present the relations of network theory and terminology. The model of scale-free networks, which has been recently developed and widely applied since, can be effectively used in terminology research as well. Operation based on the principle of networks is a universal characteristic of complex systems. Networks are governed by general laws. The model of scale-free networks can be viewed as a statistical-probability model, and it can be described with mathematical tools. Its main feature is that "everything is connected to everything else," that is, every node is reachable (in a few steps) starting from any other node; this phenomena is called "the small world phenomenon." The existence of a linguistic network and the general laws of the operation of networks enable us to place issues of language use in the complex system of relations that reveal the deeper connection s between phenomena with the help of networks embedded in each other. The realization of the metaphor that language also has a network structure is the basis of the classification methods of the terminological system, and likewise of the ways of creating terminology databases, which serve the purpose of providing easy and versatile accessibility to specialised knowledge.
    Date
    2. 9.2014 21:22:48
  6. Chung, T.M.: ¬A corpus comparison approach for terminology extraction (2003) 0.04 
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    Source
    Terminology. 9(2003) no.2, S.221-246
  7. Bernth, A.; McCord, M.; Warburton, K.: Terminology extraction for global content management (2003) 0.04 
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    Source
    Terminology. 9(2003) no.1, S.51-69
  8. Rahmstorf, G.: Concept structures for large vocabularies (1998) 0.03 
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    Abstract
    A technology is described which supports the acquisition, visualisation and manipulation of large vocabularies with associated structures. It is used for dictionary production, terminology data bases, thesauri, library classification systems etc. Essential features of the technology are a lexicographic user interface, variable word description, unlimited list of word readings, a concept language, automatic transformations of formulas into graphic structures, structure manipulation operations and retransformation into formulas. The concept language includes notations for undefined concepts. The structure of defined concepts can be constructed interactively. The technology supports the generation of large vocabularies with structures representing word senses. Concept structures and ordering systems for indexing and retrieval can be constructed separately and connected by associating relations.
    Date
    30.12.2001 19:01:22
  9. Heid, U.; Jauss, S.; Krüger, K.; Hohmann, A.: Term extraction with standard tools for corpus exploration : experience from German (1996) 0.03 
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    Source
    TKE'96: Terminology and knowledge engineering. Proceedings 4th International Congress on Terminology and Knowledge Engineering, 26.-28.8.1996, Wien. Ed.: C. Galinski u. K.-D. Schmitz
  10. Drouin, P.: Term extraction using non-technical corpora as a point of leverage (2003) 0.03 
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    Source
    Terminology. 9(2003) no.1, S.99-115
  11. ISO/DIS 1087-2:1994-09: Terminology work, vocabulary : pt.2: computational aids (1994) 0.03 
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  12. ISO/TR 12618:1994: Computational aids in terminology : creation and use of terminological databases and text corpora (1994) 0.03 
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  13. Barriere, C.: Building a concept hierarchy from corpus analysis (2004) 0.03 
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    Source
    Terminology. 10(2004) no.2, S.241-264
  14. Sager, J.A.: ¬A practical course in terminology processing : with a bibliography by Blaise Nkwenti-Azeh (1990) 0.02 
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  15. Blanchon, E.: Terminology software : pt.1.2 (1995) 0.02 
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  16. Nakagawa, H.; Mori, T.: Automatic term recognition based an statistics of compound nouns and their components (2003) 0.02 
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    Source
    Terminology. 9(2003) no.2, S.201-219
  17. Witschel, H.F.: Terminology extraction and automatic indexing : comparison and qualitative evaluation of methods (2005) 0.02 
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    Abstract
    Many terminology engineering processes involve the task of automatic terminology extraction: before the terminology of a given domain can be modelled, organised or standardised, important concepts (or terms) of this domain have to be identified and fed into terminological databases. These serve in further steps as a starting point for compiling dictionaries, thesauri or maybe even terminological ontologies for the domain. For the extraction of the initial concepts, extraction methods are needed that operate on specialised language texts. On the other hand, many machine learning or information retrieval applications require automatic indexing techniques. In Machine Learning applications concerned with the automatic clustering or classification of texts, often feature vectors are needed that describe the contents of a given text briefly but meaningfully. These feature vectors typically consist of a fairly small set of index terms together with weights indicating their importance. Short but meaningful descriptions of document contents as provided by good index terms are also useful to humans: some knowledge management applications (e.g. topic maps) use them as a set of basic concepts (topics). The author believes that the tasks of terminology extraction and automatic indexing have much in common and can thus benefit from the same set of basic algorithms. It is the goal of this paper to outline some methods that may be used in both contexts, but also to find the discriminating factors between the two tasks that call for the variation of parameters or application of different techniques. The discussion of these methods will be based on statistical, syntactical and especially morphological properties of (index) terms. The paper is concluded by the presentation of some qualitative and quantitative results comparing statistical and morphological methods.
    Source
    TKE 2005: Proc. of Terminology and Knowledge Engineering (TKE) 2005
  18. Mustafa el Hadi, W.; Jouis, C.: Natural language processing-based systems for terminological construction and their contribution to information retrieval (1996) 0.02 
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    Abstract
    This paper will survey the capacity of natural language processing (NLP) systems to identify terms or concept names related to a specific field of knowledge (construction of a reference terminology) and the logico-semantic relations they entertain. The scope of our study will be limited to French language NLP systems whose purpose is automatic terms identification with textual area-grounded terms providing access keys to information
    Source
    TKE'96: Terminology and knowledge engineering. Proceedings 4th International Congress on Terminology and Knowledge Engineering, 26.-28.8.1996, Wien. Ed.: C. Galinski u. K.-D. Schmitz
  19. L'Homme, M.-C.: Processing word combinations in existing terms banks (1995) 0.02 
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    Source
    Terminology. 2(1995) no.1, S.141-162
  20. Mustafa el Hadi, W.: Terminology & information retrieval : new tools for new needs. Integration of knowledge across boundaries (2003) 0.02 
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    Abstract
    The radical changes in information and communication techniques at the end of the 20th century have significantly modified the function of terminology and its applications in all forms of communication. The introduction of new mediums has deeply changed the possibilities of distribution of scientific information. What in this situation is the role of terminology and its practical applications? What is the place for multiple functions of terminology in the communication society? What is the impact of natural language (NLP) techniques used in its processing and management? In this article we will focus an the possibilities NLP techniques offer and how they can be directed towards the satisfaction of the newly expressed needs.

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  • m 11
  • el 9
  • s 5
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