Document (#37336)

Author

Sánchez, D.
Batet, M.
Valls, A.
Gibert, K.

Title

Ontology-driven web-based semantic similarity

Source

Journal of intelligent information systems. 35(2010) no.x, S.383-413

Year

2010

Abstract

Estimation of the degree of semantic similarity/distance between concepts is a very common problem in research areas such as natural language processing, knowledge acquisition, information retrieval or data mining. In the past, many similarity measures have been proposed, exploiting explicit knowledge-such as the structure of a taxonomy-or implicit knowledge-such as information distribution. In the former case, taxonomies and/or ontologies are used to introduce additional semantics; in the latter case, frequencies of term appearances in a corpus are considered. Classical measures based on those premises suffer from some problems: in the ?rst case, their excessive dependency of the taxonomical/ontological structure; in the second case, the lack of semantics of a pure statistical analysis of occurrences and/or the ambiguity of estimating concept statistical distribution from term appearances. Measures based on Information Content (IC) of taxonomical concepts combine both approaches. However, they heavily depend on a properly pre-tagged and disambiguated corpus according to the ontological entities in order to computer accurate concept appearance probabilities. This limits the applicability of those measures to other ontologies - like specific domain ontologies - and massive corpus - like the Web. In this paper, several of the presente issues are analyzed. Modifications of classical similarity measures are also proposed. They are based on a contextualized and scalable version of IC computation in the Web by exploiting taxonomical knowledge. The goal is to avoid the measures' dependency on the corpus pre-processing to achieve reliable results and minimize language ambiguity. Our proposals are able to outperform classical approaches when using the Web for estimating concept probabilities.

Content

Vgl.: http://www.springerlink.com/content/p115p325222u0687/fulltext.pdf.

Theme

Wissensrepräsentation

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5. Gladun, A.; Rogushina, J.: Development of domain thesaurus as a set of ontology concepts with use of semantic similarity and elements of combinatorial optimization (2021) 0.17

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