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IntegrationStategies of Meta Search Enginess

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1 IntroductionStandard Web search services are quite useful in their own right, but arefar from ideal. Search engines retrieve web pages which contain informationrelative to the subject which the user queries. Meta search unlike standardsearch, utilizes many di erent search systems to provide results. The MetaSearch Engine (MSE) is a system that enables a meta search[3].

Meta search engines are Web services that receive user queries and dispatchthem to multiple crawl-based search engines (also called componentengines)[1]. Once all the results are returned from the component search engines,they are merged into a single ranked list.

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The advantage of MSEs aretheir ability to combine coverage across multiple search engines thus allowingthem to reach the Deep Web. MSEs therefore work at a much higher levelthan the standard web search engine.

There are two distinct steps in creating a MSE. Firstly searching throughthe deep web to collect results and secondly to both merge and rank thoseresults. Thus the algorithm used in the ranking and merging process iscritical because it has a direct impact on the e ectiveness of the MSE.

Thisreport will focus on discussing di erent strategies to integrate the resultsreceived from multiple search engines for use in a MSE.

2 Meta Search Engine SystemIn order for us better understand result integration strategies, we need to takea look the science involved in creating a MSE. These can also be consideredstrategies which help the MSE return better search results. There are threecomponents to take into consideration when building a MSE these includesearch engine selection,result extraction and result integration.

2.1 Search Engine SelectionIn order for the MSE to chose which search e.

. .sadvantage is if a user is English speaking andsearches for the a hotel in China the resulting pages may be in a di erentlanguage possibly Mandarin of domain name .cn. This method is highlypersonalised to queries of a geographical nature as compared to the othermethods described above.

Works CitedLeonidas Akritidis, Dimitrios Katsaros, and Panayiotis Bozanis. E ectiveranking fusion methods for personalized metasearch engines.

Javed A. Aslam and Mark Montague. Models for metasearch.

Hossein Jadidoleslamy. Search result merging and ranking strategies inmeta-search engines: A survey, 2012. Yiyao Lu, Weiyi Meng, Liangcai Shu, Clement Yu, and King lup Liu.

Evaluation of result merging strategies for metasearch engines. In WISEConference, pages 53{66, 2005.

M. Elena Renda and Umberto Straccia. Web metasearch: Rank vs. scorebased rank aggregation methods, 2003.

Cite this IntegrationStategies of Meta Search Enginess

IntegrationStategies of Meta Search Enginess. (2018, Feb 02). Retrieved from https://graduateway.com/integrationstategies-of-meta-search-engines-essays/

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