Google scholar arxiv informatics ads IJAIS publications are indexed with Google Scholar, NASA ADS, Informatics et. al.

Call for Paper

-

July Edition 2022
International Journal of Applied Information Systems solicits high quality original research papers for the July 2022 Edition of the journal. The last date of research paper submission is June 15, 2022.

Concept based Web Information Retrieval

Jyotsna Gharat, Jayant Gadge Published in Information Sciences

Concept based Web Information Retrieval
International Journal of Applied Information Systems
Year of Publication 2012
© 2010 by IJAIS Journal
Series Volume 4 Number 5
Authors Jyotsna Gharat, Jayant Gadge
10.5120/ijais12-450713
Download full text

  1. Jyotsna Gharat and Jayant Gadge. Article: Concept based Web Information Retrieval. International Journal of Applied Information Systems 4(5):25-29, October 2012. BibTeX

    @article{key:article,
	author = "Jyotsna Gharat and Jayant Gadge",
	title = "Article: Concept based Web Information Retrieval",
	journal = "International Journal of Applied Information Systems",
	year = 2012,
	volume = 4,
	number = 5,
	pages = "25-29",
	month = "October",
	note = "Published by Foundation of Computer Science, New York, 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.

Reference

  1. 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. .
  2. 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.
  3. 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.
  4. 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.
  5. George A. Miller, "WordNet: A Lexical Database for English", Communications of the ACM, Vol. 38, No. 11, pp. 39-41, 1995.
  6. Measuring Similarity between sentences. [Online]. Available at: http://wordnetdotnet. googlecode. com/svn /trunk/Projects/Thanh/Paper/WordNetDotNet_Semantic_Similarity. pdf.
  7. WordNet Documentation. [Online]. Available at: http://wordnet. princeton. . edu/man2. 1/wnstats. 7WN.
  8. What is Stemming? [Online]. Available at: http://www. comp. lancs. ac. uk/computing/research/stemming/general.
  9. Important problems in information retrieval. Dagobert Soergel, College of Library and Information Services, University of Maryland, College Park, MD 20742, August 1989.
  10. G. Salton and C. Buckley, "Term – Weighting Approaches in Automatic Text Retrieval", Information Processing and Management, vol. 24, no. 5, pp. 513 – 523, 1988.

Keywords

Information Retrieval (IR), Part of Speech (POS), WordNet, Ontology, Concept-Based Term Weighting (CBW)