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Merging Multiple Search Results Approach for Meta-Search Engines

Mohamed, Khaled Abd El-Fatah (2006) Merging Multiple Search Results Approach for Meta-Search Engines. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Meta Search Engines are finding tools developed for enhancing the search performance by submitting user queries to multiple searchengines and combining the search results in a unified ranked list. They utilized data fusion technique, which requires three major steps: databases selection, the results combination, and the results merging. This study tries to build a framework that can be used for merging the search results retrieved from any set of search engines. This framework based on answering three major questions:1.How meta-search developers could define the optimal rank order for the selected engines.2. How meta-search developers could choose the best search engines combination.3.What is the optimal heuristic merging function that could be used for aggregating the rank order of the retrieved documents form incomparable search engines.The main data collection process depends onrunning 40 general queries on three major search engines (Google, AltaVista, and Alltheweb). Real users have involved in the relevance judgment process for a five point relevancy scale. Theperformance of the three search engines, their different combinations and different merging algorithm have been compared to rank the database, choose the best combination and define the optimal merging function.The major findings of this study are (1) Ranking the databases in merging process should depends on their overall performance not their popularity or size; (2)Larger databases tend to perform better than smaller databases; (3)The combination of the search engines should depend on ranking the database and choosing theappropriate combination function; (4)Search Engines tend to retrieve more overlap relevant document than overlap irrelevant documents; and (5) The merging function which take theoverlapped documents into accounts tend to perform better than the interleave and the rank similarity function.In addition to these findings the study has developed a set of requirements for the merging process to be successful. This procedure include the databases selection, the combination, and merging upon heuristic solutions.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Mohamed, Khaled Abd
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairTomer, Christingerctomer@pitt.eduCTOMER
Committee MemberKnapp, Amyaknapp@pitt.eduAKNAPP
Committee MemberKing, Donalddwking
Committee MemberGriffiths, José-Mariejmgriff
Date: 31 January 2006
Date Type: Completion
Defense Date: 29 January 2004
Approval Date: 31 January 2006
Submission Date: 3 February 2004
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Library and Information Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: combination; combining retreived documents; Data Fusion; experimental method; Information Retrieval; merging Algorithm; Meta-Engines; Meta-Search Engines; rank aggregation; resources combination; retieval experiment; Web Retrieving; world wide web; www
Other ID:, etd-02032004-163252
Date Deposited: 10 Nov 2011 19:31
Last Modified: 15 Nov 2016 13:36


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