JOURNAL ARTICLE

Semantic Information Retrieval based on Wikipedia Taxonomy

May Sabai Han

Year: 2012 Journal:   International Journal of Computer Applications Technology and Research Vol: 2 (1)Pages: 77-80

Abstract

Information retrieval is used to find a subset of relevant documents against a set of documents.Determining semantic similarity between two terms is a crucial problem in Web Mining for such applications as information retrieval systems and recommender systems.Semantic similarity refers to the sameness of two terms based on sameness of their meaning or their semantic contents.Recently many techniques have introduced measuring semantic similarity using Wikipedia, a free online encyclopedia.In this paper, a new technique of measuring semantic similarity is proposed.The proposed method uses Wikipedia as an ontology and spreading activation strategy to compute semantic similarity.The utility of the proposed system is evaluated by using the ta xonomy of Wikipedia categories.

Keywords:
Computer science Information retrieval Taxonomy (biology) World Wide Web Natural language processing

Metrics

9
Cited By
1.89
FWCI (Field Weighted Citation Impact)
13
Refs
0.89
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Wikis in Education and Collaboration
Social Sciences →  Social Sciences →  Communication
© 2026 ScienceGate Book Chapters — All rights reserved.