Research Article
Concept based Web Information Retrieval
|
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
|
| Volume 4 - Issue 5 |
| Published: October 2012 |
| Authors: Jyotsna Gharat, Jayant Gadge |
10.5120/ijais12-450713
|
Jyotsna Gharat, Jayant Gadge . Concept based Web Information Retrieval. International Journal of Applied Information Systems. 4, 5 (October 2012), 25-29. DOI=10.5120/ijais12-450713
@article{ 10.5120/ijais12-450713,
author = { Jyotsna Gharat,Jayant Gadge },
title = { Concept based Web Information Retrieval },
journal = { International Journal of Applied Information Systems },
year = { 2012 },
volume = { 4 },
number = { 5 },
pages = { 25-29 },
doi = { 10.5120/ijais12-450713 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2012
%A Jyotsna Gharat
%A Jayant Gadge
%T Concept based Web Information Retrieval%T
%J International Journal of Applied Information Systems
%V 4
%N 5
%P 25-29
%R 10.5120/ijais12-450713
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Information retrieval is concerned with documents relevant to a user's information needs from a collection of documents. The user describes information needs with a query which consists of a number of words. Finding weight of a query is important to determine importance of a query. Calculating term importance is fundamental aspect of most information retrieval approaches and it is commonly determined through Term Frequency- Inverse Document Frequency (TF-IDF). This paper proposed Concept-based Term Weighting (CBW) technique to determine the term importance by finding the weight of a query. WordNet ontology is used to find the conceptual information of each word in the query.
References
- Che-Yu Yang; Shih-Jung Wu, "A WordNet based Information Retrieval on the Semantic Web", Networked Computing and Advanced Information Management (NCM), 2011 7th International Conference, Page(s): 324 – 328, 2011. .
- Zakos, J. ; Verma, B. , "Concept-based term weighting for web information retrieval", Computational Intelligence and Multimedia Applications, 2005. Sixth International Conference, Page(s): 173 – 178, 2005.
- Jiuling Zhang; Beixing Deng; Xing Li, "Concept Based Query Expansion using WordNet", Advanced Science and Technology, 2009. AST '09. International e-Conference, Page(s): 52 - 55, 2009.
- Zhen-Yu Lu; Yong-Min Lin; Shuang Zhao; Jing-Nian Chen; Wei-Dong Zhu, "A Redundancy Based Term Weighting Approach for Text Categorization", Software Engineering, 2009. , Page(s): 36 – 40, 2009.
- George A. Miller, "WordNet: A Lexical Database for English", Communications of the ACM, Vol. 38, No. 11, pp. 39-41, 1995.
- Measuring Similarity between sentences. [Online]. Available at: http://wordnetdotnet. googlecode. com/svn /trunk/Projects/Thanh/Paper/WordNetDotNet_Semantic_Similarity. pdf.
- WordNet Documentation. [Online]. Available at: http://wordnet. princeton. . edu/man2. 1/wnstats. 7WN.
- What is Stemming? [Online]. Available at: http://www. comp. lancs. ac. uk/computing/research/stemming/general.
- Important problems in information retrieval. Dagobert Soergel, College of Library and Information Services, University of Maryland, College Park, MD 20742, August 1989.
- G. Salton and C. Buckley, "Term – Weighting Approaches in Automatic Text Retrieval", Information Processing and Management, vol. 24, no. 5, pp. 513 – 523, 1988.
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