About QuadSearch    

Metasearch engines are Web services designed to transfer the user queries to multiple existing search engines (called component engines). A metasearch engine does not maintain its own index of documents. It collects and reorganizes the result lists (top-k lists), then it returns the processed data to the user.

Compared to a standard single search engine, a metasearch engine offers:

  • Increased web coverage
  • Improved retrieval effectiveness
  • Effortless invocation of multiple search engines

QuadSearch is a constantly evolving metasearch engine designed to serve as a testbed for evaluating and developing rank aggregation, data fusion and result clustering methods. It is hosted by the Raptor Web server, which belongs to the Data Engineering Laboratory (DELAB), of Aristotle University of Thessaloniki.

It has been created by Leonidas Akritidis, George Voutsakelis, Dimitrios Katsaros and Panayiotis Bozanis.

Their main purpose is to build a powerful scientific tool, that will be used by the academic community in order to retrieve useful information. Their secondary objective focuses on finding better and faster rank aggregation and data fusion methods.

QuadSearch's heart is the KE Algorithm, which is the mechanism that determines the classification of the collected results. KE Algorithm was invented by the founders of this engine and has also been the basis for Search Engine Analyzer. Apart from KE Algorithm, QuadSearch is capable of using a variety of several other ranking algorithms to organize the collected results. You can select among many rank aggregation methods by visiting the Options page.

QuadSearch is constantly under construction. If you have any suggestions for it, or you want to report a security issue, please let us know, by filling the appropriate contact form.

  • QuadRank Method: Leonidas Akritidis, Dimitrios Katsaros, Panayiotis Bozanis. "Effective Rank Aggregation for Metasearching", Journal of Systems and Software, Elsevier, vol. 84, no 1, pp 130-143, January 2011.
  • KE Algorithm: Leonidas Akritidis, George Voutsakelis, Dimitrios Katsaros, Panayiotis Bozanis. "QuadSearch: A novel metasearch engine", In Proceedings of the 11th Panhellenic Conference on Informatics (PCI), pp. 453-466, Patras, Greece, May 18-20, 2007.
  • Geography Aware KE and Domain Aware KE Algorithms: Leonidas Akritidis, Dimitrios Katsaros, Panayiotis Bozanis. "Effective Ranking Fusion Methods for Personalized Metasearch Engines", In Proceedings of the Panhellenic Conference on Informatics (PCI), IEEE Press, pp. 39-43, Samos Island, Greece, August 28-30, 2008.
  • Borda Count Method: J. C. Borda. "Memoire sur les elections au scrutin", Histoire de l'Academie Royale des Sciences, 1781.
  • Footrule Optimal Aggregation: J. I. Marden. "Analyzing and Modeling Rank Data", Number 64 in Monographs on Statistics and Applied Probability. Chapman & Hall, 1995.
  • Linear Combination Methods: E. A. Fox and J. A. Shaw. "Combination of multiple searches", In Proceedings of TREC'3. NIST Publication, 1994.
  • Condorcet Method: Marquis de Condorcet. "Essai sur l'application de l'analyse á la probabilité des décisions rendues á la pluralité des voix", Imprimerie Royale, Paris, 1785.
  • Markov Chains Method: Cynthia Dwork, Ravi Kumar, Moni Naor, D. Sivakumar. "Rank aggregation methods for the Web", In Proceedings of the 10th international conference on World Wide Web, p.613-622, May 01-05, 2001, Hong Kong, Hong Kong
  • Outranking Method: Mohamed Farah, Daniel Vanderpooten. "An Outranking Approach for Rank Aggregation in Information Retrieval", In Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, 2007, pp. 591-598, Amsterdam, The Netherlands.
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