e-ISSN : 0975-3397
Print ISSN : 2229-5631
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ABSTRACT

Title : Lexico-syntactic and Semantic Patterns for Extracting Knowledge from Persian Texts
Authors : Mehnroush Shamsfard
Keywords : knowledge extraction; linguistic patterns; taxonomic relations; ontology learning; Persian text processing
Issue Date : September 2010
Abstract :

In recent years, knowledge extraction from texts is focused to overcome to bottleneck of building ontologies for semantic web. Pattern based, template driven and linguistic methods are among the successful approaches to extract ontological knowledge from raw texts. This paper introduces some lexico-syntactic and semantic patterns and templates for extracting conceptual knowledge from Persian texts. The described patterns are general and domain/ application independent and work at sentence level. They are used to extract taxonomic and non-taxonomic relations and axioms from phrases and sentences. Among the introduced patterns and templates, semantic patterns are language independent and although linguistic (lexico-syntactic) patterns are introduced for Persian language, they could easily be adopted to other languages such as English.

This paper will first have a brief overview on linguistic and template driven methods to discover ontological knowledge from texts. Then the templates for Persian simple sentences will be introduced. The extracted relations may be hyponymy, meronymy, attribute/value, part-of, equivalency, etc. The introduced templates exploit semantic information to not only extract the instances of predefined relations (the concepts related by them), but also define new relations. In each case some examples of the experimental results will make the patterns clear.

Page(s) : 2190-2196
ISSN : 0975–3397
Source : Vol. 2, Issue.6

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