Semantic ambiguous query formulation using statistical Linguistics technique

Abdul Kadir Rabiah, Rufai Aliyu Yauri, Azreen Azman

Research output: Contribution to journalArticle

Abstract

Natural language query systems mitigate the complexity of structured query. Usually, natural language processing is implemented to solve several problems, such as information retrieval. However, problems such as natural language ambiguity remain unsolved due to the complexity of natural language itself. This issue thus requires further research. Recent studies on semantic query formulation have attempted to resolve ambiguous natural language by proposing different disambiguation approaches. Most such processes are either implemented manually or semi-automated. In the same vein, most recent systems solve ambiguity by using an external dictionary such as WordNet or by providing suggestions manually. The present research proposes a statistical linguistic technique for solving the problem of ambiguity automatically. The proposed technique is experimentally tested on a Quran ontology with queries from the Islamic Research Foundation Website and increases the result of precision and recall by 6% and 10%, respectively.

Original languageEnglish
Pages (from-to)48-56
Number of pages9
JournalMalaysian Journal of Computer Science
Volume31
Issue number5
DOIs
Publication statusPublished - 1 Jan 2018

Fingerprint

Computational linguistics
Semantics
Query languages
Glossaries
Information retrieval
Ontology
Websites
Processing

Keywords

  • Information retrieval
  • Islamic knowledge
  • Ontology
  • Semantic technology
  • Statistical linguistics technique

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Semantic ambiguous query formulation using statistical Linguistics technique. / Rabiah, Abdul Kadir; Yauri, Rufai Aliyu; Azman, Azreen.

In: Malaysian Journal of Computer Science, Vol. 31, No. 5, 01.01.2018, p. 48-56.

Research output: Contribution to journalArticle

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