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General Information
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2013 Vol.3(4): 357-360 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.337

An Application of Topic Map-Based Ontology Generated from Wikipedia for Query Expansion

S. Eslami and E. Nazemi
Abstract—Topic maps are a Semantic Web technology for semantic annotation of resources to enhance the quality of search output. The main idea of this research is to present a query expansion method using topic maps-based ontology for query expansion process, furthermore this paper proposed a novel automatic approach to construct topic maps from Wikipedia XML corpus. Wikipedia is general purpose, freely available online, is containing up to date information so it is a suitable option for topic map development. The proposed model is implemented and then applied on a test collection. The results show that using topic map-based ontology in query expansion process improves search accuracy in keyword-based information retrieval.

Index Terms—Ontology, information retrieval, semantic web, topic maps, query expansion.

Saeedeh Eslami is now with the National Library and Archive of Iran Tehran, Iran (e-mail: s-eslami@nlai.ir, eslami.saeedeh@gmail.com, phone: +9881622440). Eslam Nazemi was with Shahid Beheshti University (SBU), Tehran, Iran. He is now with the Electrical and Computer Engineering Faculty (e-mail: nazemi@sbu.ac.ir).


Cite:S. Eslami and E. Nazemi, "An Application of Topic Map-Based Ontology Generated from Wikipedia for Query Expansion," International Journal of Machine Learning and Computing vol.3, no. 4, pp. 357-360, 2013.

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