Information Retrieval in Wikis Using an Ontology

This article addresses a question regarding relevant information in a social media such as a wiki that can contain huge amount of text, written in slang or in natural language, without necessarily observing a fixed terminology set. This text could not always be adherent to the discussed subject. The...

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Bibliographic Details
Published in2009 International Conference on Computational Science and Engineering Vol. 4; pp. 826 - 831
Main Authors Tobar, C.M., Germer, A.S., Adan-Coello, J.M., de Freitas, R.L.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2009
Subjects
Customer satisfaction
Data mining
Information retrieval
Java
Natural languages
Ontologies
Ontology
Semantic Web
Social media
Software tools
Terminology
Wiki
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Summary:This article addresses a question regarding relevant information in a social media such as a wiki that can contain huge amount of text, written in slang or in natural language, without necessarily observing a fixed terminology set. This text could not always be adherent to the discussed subject. The main motivation leads to the need of developing methods that would allow the extraction of relevant information in such scenario. A result system was designed upon ideas from the semantic Web combined with an adaptation of the classic vector model for information retrieval. The semantic information is not embedded in the media but within a structurally independent ontology. It was implemented using Java and a MySQL database. The objective was the achievement of, at least, 80% for recall and precision on the system results. The system was considered successful by achieving rates of 100% of recall and approximately 93% of precision.
ISBN:9781424453344
1424453348
DOI:10.1109/CSE.2009.285