Automated semantic query formulation using machine learning approach

Abdul Kadir Rabiah, Aliyu Rufai Yauri

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Search engines such Yahoo and Google among others has played significant role Web data access. However these search engines has limitations. These search engines are based on a keyword search which lacks semantics in the retrieval process. To cope with the Limitations of current search engines, Semantic Web was introduced. Semantic Web enables retrieval of data on the Web semantically. In semantic Web, data is standardised in a format that enables retrieval of such data semantically. But Semantic Web also has challenges where retrieval requires complex structured query such as SPARQL which is not simple are using Google like natural language query. This paper presents an approach of automatic semantic query formulation that enables retrieval of semantically structured data using natural language. The proposed approach is based on using machine learning and the result has shown improvement of 17.4% compared to existing approach in FREyA in terms of effectiveness formulated natural language queries to structured query.

Original languageEnglish
Pages (from-to)2761-2775
Number of pages15
JournalJournal of Theoretical and Applied Information Technology
Volume95
Issue number12
Publication statusPublished - 30 Jun 2017

Fingerprint

Search engines
Semantic Web
Learning systems
Machine Learning
Retrieval
Search Engine
Semantics
Query
Formulation
Query languages
Natural Language
SPARQL
Keyword Search
World Wide Web

Keywords

  • Machine learning
  • Ontology
  • Quran
  • Semantic web

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Automated semantic query formulation using machine learning approach. / Rabiah, Abdul Kadir; Yauri, Aliyu Rufai.

In: Journal of Theoretical and Applied Information Technology, Vol. 95, No. 12, 30.06.2017, p. 2761-2775.

Research output: Contribution to journalArticle

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