List of Journals    /    Call For Papers    /    Subscriptions    /    Login
 
 
 
 
 SEARCH
By Author By Title
 
 
ABOUT CSC
 About CSC Journals
 CSC Journals Objectives
 List of Journals
 CALL FOR PAPERS
 Call For Papers CFP
 Special Issue CFP
AUTHOR GUIDELINES
 Submission Guidelines
 Peer Review Process
 Helpful Hints For Getting Published
 Plagiarism Policies
 Abstracting & Indexing
 Open Access Policy
 Submit Manuscript
 FOR REVIEWERS
 Reviewer Guidelines
 FOR EDITORIAL
 Editor Guidelines
 Join Us As Editor
 Launch Special Issue
 Suggest New Journal
 CSC LIBRARY
 Browse CSC Library
 Open Access Policy
  SERVICES
 Conference Partnership Program (CPP)
 Abstracting & Indexing
 SUBSCRIPTIONS
 Subscriptions
 Discounted Packages
 Archival Subscriptions
 How to Subscribe
 Librarians
 Subscriptions Agents
 Order Form
 DOWNLOADS
 
 
 
 
Comparison of Semantic and Syntactic Information Retrieval System on the basis of Precision and Recall
Full text
 PDF(273.9KB)
Source 
International Journal of Data Engineering (IJDE)
Table of Contents
Download Complete Issue    PDF(960.43KB)
Volume:  2    Issue:  3
Pages:  NULL
Publication Date:   July / August 2011
ISSN (Online): 2180-1274
Pages 
93 - 101
Author(s)  
Deepak - India
Sanchika - India
 
Published Date   
05-08-2011 
Publisher 
CSC Journals, Kuala Lumpur, Malaysia
ADDITIONAL INFORMATION
Keywords   Abstract   References   Cited by   Related Articles   Collaborative Colleague
 
KEYWORDS:   Information Retrieval, Precision, Recall, Semantic 
 
 
This Manuscript is indexed in the following databases/websites:-
1. Google Scholar
2. Scribd
 
 
In this paper information retrieval system for local databases are discussed. The approach is to search the web both semantically and syntactically. The proposal handles the search queries related to the user who is interested in the focused results regarding a product with some specific characteristics. The objective of the work will be to find and retrieve the accurate information from the available information warehouse which contains related data having common keywords. This information retrieval system can eventually be used for accessing the internet also. Accuracy in information retrieval that is achieving both high precision and recall is difficult. So both semantic and syntactic search engine are compared for information retrieval using two parameters i.e. precision and recall. 
 
 
 
1 C.D. Manning, P. Raghavan, H. Schütze. “An Introduction to information retrieval”, Cambridge University Press Cambridge, England, Apr 1, 2009, pp. 26- 569.
2 World Wide Web Consortium. “OWL Web Ontology Language Semantics and Abstract Syntax”. W3C Recommendation 10 Feb, 2004.
3 H. Knublauch, M. A. Musen, A. L. Rector. Medical Informatics Group, “Editing Description Logic Ontologies with the Protege OWL Plugin”, Stanford University and University of Manchester, pp. 1- 9.
4 M. Horridge, H. Knublauch, A. Rector, R. Stevens, C. Wroe. “A Practical Guide To Building OWL Ontologies Using The Prot´eg´e-OWL Plugin and CO-ODE Tools Edition 1.0”, The University Of Manchester, 2004.
5 World wide web consortium Internet: http://www.w3.org/2001, 2001.
6 V. David, F. Miriam, C. Pablo. “An Ontology Based Information Retrieval Model” Universidad Autonoma de Madrid.
7 J. Bar-Ilan. “On the overlap, the precision and estimated recall of search engines: A case study of the query "Erdos"”. Scientometrics, 42 (2), 207-208, 1998.
8 H. Chu, M. Rosenthal. (1996). “Search engines for the World Wide Web: a comparative study and evaluation methodology” Proceedings of the ASIS 1996 Annual Conference. [online] Available: http://www.asis.org/annual96/ElectronicProceedings/chu.html. October, 33. 127-35. Retrieved August 19, 2003.
9 S. Clarke, P. Willett. “Estimating the recall performance of search engines”. ASLIB Proceedings, 49 (7), pp. 184-189, 1997.
10 W. Ding, G. Marchionini. “A comparative study of the Web search service performance”. In: Proceedings of the ASIS 1996 Annual Conference, Oct 1996, pp.136-142.
11 C. Oppenheiem, A. Moris, C. Mcknight, S. Lowley. “The evaluation of WWW search engines”. Journal of documentation, 56 (2), pp.190-211, 2000.
12 C. Cesarano, A. d’Acierno, A. Picariello. “An Intelligent Search Agent System for Semantic Information Retrieval on the Internet”. WIDM’03, , New Orleans, Louisiana, USA. Nov 7–8, 2003.
13 E. HyvÄonen, A. Styrman, S. Saarela. “Ontology-Based Image Retrieval”, University of Helsinki, Department of Computer Science, pp.1-13.
14 H. Sumiyoshi, I. Yamada, Y. Murasaki, Y.B. Kim, N. Yagi and M. Shibata, "Agent Search System for A New Interactive Education Broadcast Service", NHK STRL R&D No.84, Mar, 2004.
15 Guo-Qiang Zhang, Adam D. Troy, and Keith Bourgoin. “Bootstrapping Ontology Learning for Information Retrieval Using Formal Concept Analysis and Information Anchors”, Department of Electrical Engineering and Computer Science Case Western Reserve University Cleveland, Ohio 44106, U.S.A, pp.1-14, 2008.
 
 
 
 
 
 
 
 
Deepak : Colleagues
Sanchika : Colleagues  
 
 
 
  Untitled Document
 
Copyrights (c) 2012 Computer Science Journals. All rights reserved.
Best viewed at 1152 x 864 resolution. Microsoft Internet Explorer.
 
  
 
Copyrights & Usage: Articles published by CSC Journals are Open Access. Permission to copy and distribute any other content, images, animation and other parts of this website is prohibited. CSC Journals has the rights to take action against individual/group if they are found victim of copying these parts of the website.