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
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: email@example.com, firstname.lastname@example.org, phone: +9881622440). Eslam Nazemi was with Shahid Beheshti University (SBU), Tehran, Iran. He is now with the Electrical and Computer Engineering Faculty (e-mail: email@example.com).
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.