DocumentCode :
2921683
Title :
Enriching non-taxonomic relations extracted from domain texts
Author :
Nabila, N.F. ; Mamat, A. ; Azmi-Murad, M.A. ; Mustapha, N.
Author_Institution :
Fac. of Sci. & Technol., Univ. Sains Islam Malaysia, Nilai, Malaysia
fYear :
2011
fDate :
28-29 June 2011
Firstpage :
99
Lastpage :
105
Abstract :
Extracting non-taxonomic relations is one of the important tasks in the construction of ontology from the text. Most of current methods on identification and extraction of non-taxonomic relations is based on predicate representing relationships between two concepts, namely the relation between subject and object that occurs in a sentence. However, the number of relations that has been identified does not properly represent the domain as the methods only identify a portion of the total relations from domain texts. In this paper, we present a method that increases the number of relations extracted and thus properly represent the domain. In this method, all potential relations are first generated and then less significant ones, based on their frequency, are removed. The method has been tested on a collection of texts that described electronic voting machine and the result is encouraging.
Keywords :
government data processing; ontologies (artificial intelligence); text analysis; domain text extraction; electronic voting machine; nontaxonomic relation extraction; ontology construction; potential relations; text collection; Association rules; Companies; Frequency domain analysis; Labeling; Object recognition; Ontologies; Non-taxonomic relation; Relation Extraction; Relation Identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Semantic Technology and Information Retrieval (STAIR), 2011 International Conference on
Conference_Location :
Putrajaya
Print_ISBN :
978-1-61284-354-4
Electronic_ISBN :
978-1-61284-353-7
Type :
conf
DOI :
10.1109/STAIR.2011.5995772
Filename :
5995772
Link To Document :
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