Call for Paper - May 2023 Edition
IJCA solicits original research papers for the May 2023 Edition. Last date of manuscript submission is April 20, 2023. Read More

Design and Development of a Programmable Meta Search Engine

International Journal of Computer Applications
© 2013 by IJCA Journal
Volume 74 - Number 5
Year of Publication: 2013
Manoj M
Elizabeth Jacob

Manoj M and Elizabeth Jacob. Article: Design and Development of a Programmable Meta Search Engine. International Journal of Computer Applications 74(5):6-11, July 2013. Full text available. BibTeX

	author = {Manoj M and Elizabeth Jacob},
	title = {Article: Design and Development of a Programmable Meta Search Engine},
	journal = {International Journal of Computer Applications},
	year = {2013},
	volume = {74},
	number = {5},
	pages = {6-11},
	month = {July},
	note = {Full text available}


To the web user, a Meta Search Engine (MSE) appears much like a regular search engine (SE). MSE, unlike an SE does not have an index. Instead, it dynamically queries multiple search engines; extracts, fuses and re-ranks results and presents to users. Generally, an MSE is developed from scratch even if the focus is on improving fusion ranking, query modification or domain specific search. This paper proposes a programmable MSE with the help of a LISP-like language called T! for interfacing search sources and for modifying fused results. This enables easy construction and deployment of an MSE service. The Programmable-Meta Search Engine (P-MSE) provides, but is not limited to the following new features: construction of a domain specific vertical or general MSE by addition of dynamic web pages as front-end; a tool for fully automated test-run of various fusion algorithms and query modification schemes using a program or script capable of http-querying as front-end on real-time web; a programmable service where account holders can upload scripts and deploy meta search engines. The concept of P-MSE developed here, is showcased by the MSE called SSIR (SSIR for the Savvy Information Retriever).


  • Chau, M. , Chen, H. , Qin, J. , Zhou, Y. , Qin, Y. , Sung W. , and McDonald, D. 2002. Comparison of Two Approaches to Building a Vertical Search Tool: A Case Study in the Nanotechnology Domain. In Proceedings of JCDL'02, Portland, OR, USA (July 2002)
  • Chen, H. , Fan, H. , Chau M. , and Zeng, D. 2003. Testing a Cancer Meta Spider; International Journal of Human-Computer Studies (IJHCS). 59(5), 755-776.
  • http://trec. nist. gov/, Text REtrieval Conference Home Page, (Accessed 20 Feb. 2013).
  • Majumder, P. , Mitra, M. , Pal, D. , Bandyopadhyay, A. , Maiti, S. , Mitra, S. , Sen A. , and Pal, S. 2008. Text collections for FIRE. In Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '08). ACM, New York, NY, USA, 699-700.
  • Manoj, M. , and Jacob, E. 2008. Information retrieval on Internet using meta-search engines: A review, Journal of Scientific & Industrial Research. 67(10), 739-746.
  • Selberg, E. W. 1999. Towards Comprehensive Web Search. Ph. D. thesis, University of Washington.
  • Glover, E. J. 2001. Using Extra-Topical User Preferences to Improve Web-Based Metasearch. Ph. D. thesis, University of Michigan.
  • Naz, T. 2009. Configurable Meta-search in the Human Resource Domain. PhD thesis, Vienna University of Technology.
  • Voorhees, E. M. , Gupta, N. K. and Johnson-Laird, B. 1995. The Collection Fusion Problem. In Proceedings of the Third Text Retrieval Conference (TREC-3); 95-104.
  • Vogt, C. C. 1999. Adaptive Combination of Evidence for Information Retrieval. Ph. D. Thesis, University of California, San Diego.
  • Montague, M. 2002. Metasearch: Data Fusion for Document Retrieval. Ph. D. thesis, Dartmouth College.
  • Nassar M. O. , and Kanaan, G. 2009. fCombMNZ: an Improved Data Fusion Algorithm. In Proceedings of the International Conference on Information Management and Engineering, Kuala Lumpur, Malaysia April 03-April 05, 461-464.
  • Chowdhury, A. and Soboroff, I. 2002. Automatic evaluation of World Wide Web search services, In Proceedings of SIGIR-2002. 421-422.
  • Jensen, E. C. 2006. Repeatable Evaluation of Information Retrieval Effectiveness in Dynamic Environments. Ph. D Thesis, Illinois Institute of Technology, Chicago, Illinois.
  • Jensen, E. C. , Beitzel, S. M. , Chowdhury A. , and Frieder, O. 2007. Repeatable evaluation of search services in dynamic environments, ACM Transactions on Information Systems (TOIS). 26(1), 1-38
  • Nuray R. , and Can, F. 2006. Automatic ranking of information retrieval systems using data fusion, Information Processing and Management. 42(3), 595-614.
  • http://tools. seobook. com/authority-finder/myriad. txt, Myriad Meta Search Engine Source Code, (Accessed 20 Feb. 2013).
  • http://sourceforge. net/projects/chalipa/, Chalipa Meta Search Engine - Open Source Project, (Accessed 20 Feb. 2013).
  • http://web. archive. org/web/20070927230954/http://fravia. com/nbbw. c, Scroogle Source Code, (Accessed 20 Feb. 2013).
  • Gulli A. , and Signorini A. 2005. Building an Open Source Meta Search Engine. In Proceedings of 14th International World Wide Web Conference, (Chiba, Japan), 1004–1005.
  • Ferragina P. , and Gulli, A. 2008. A personalized search engine based on Web-snippet hierarchical clustering. Software: Practice and Experience, 38 (2), 189-225.
  • Guha, R. V. 2005. Programmable search engine. U. S. patent (10 Aug 2005).
  • Manoj, M. , and Jacob. E. 2010. Analysis of Meta-Search engines using the Meta-Meta-Search tool SSIR. International Journal of Computer Applications. 1(6), 10–16