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Inbenta Semantic Search Engine: a search engine inspired by the Meaning-Text Theory

Published: 13 June 2016 Publication History

Abstract

Due to the widespread digitalization of documents, the need to build sophisticated search engines that can adapt to the particular way users ask questions and provide quick and efficient access to information is becoming increasingly relevant.
To cope with this reality, INBENTA has developed an intelligent search engine, called the Inbenta Semantic Search Engine (ISSE). ISSE's two main tasks are analyzing users' queries and finding the most appropriate answer to those questions in a knowledge-base. To carry out these tasks, INBENTA's software solution relies on Meaning-Text Theory, which focuses on the lexicon and semantics.

References

[1]
Mel'Cuk, I., Polguere, A. (1995) Introduction à la lexicologie explicative et combinatoire. Bruxelles: Duculot.
[2]
Mel'Cuk, I. (2003) Collocations dans le dictionnaire, Les écarts culturels dans les Dictionnaires bilingues, Paris: Honoré Champion, p. 19--64,
[3]
Saint-Dizier, P. (2002) Quelques défis et éléments de méthode pour la construction de ressources lexicales sémantiques, Revue française de linguistique appliquée I (Vol. VII), p 39--51
[4]
Strigin, A. (1998): Lexical Rules as Hypothesis Generators. Journal of Semantics 15.
  1. Inbenta Semantic Search Engine: a search engine inspired by the Meaning-Text Theory

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      WIMS '16: Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics
      June 2016
      309 pages
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      New York, NY, United States

      Publication History

      Published: 13 June 2016

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      Author Tags

      1. Meaning-Text Theory
      2. Natural language processing
      3. Search engine
      4. lexical function
      5. lexicon
      6. semantics

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      WIMS '16 Paper Acceptance Rate 36 of 53 submissions, 68%;
      Overall Acceptance Rate 140 of 278 submissions, 50%

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