Integration Stategies of Meta Search Engines

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1 Introduction
Standard Web search services are quite useful in their own right, but are far from ideal. Search engines retrieve web pages which contain information relative to the subject which the user queries. Meta search unlike standard search, utilizes many di erent search systems to provide results. The Meta
Search Engine (MSE) is a system that enables a meta search[3].
Meta search engines are Web services that receive user queries and dispatch them to multiple crawl-based search engines (also called component engines)[1]. Once all the results are returned from the component search engines, they are merged into a single ranked list. The advantage of MSEs are their ability to combine coverage across multiple search engines thus allowing them to reach the Deep Web. MSEs therefore work at a much higher level than the standard web search engine.
There are two distinct steps in creating a MSE. Firstly searching through the deep web to collect results and secondly to both merge and rank those results. Thus the algorithm used in the ranking and merging process is critical because it has a direct impact on the e ectiveness of the MSE. This report will focus on discussing di erent strategies to integrate the results received from multiple search engines for use in a MSE.
2 Meta Search Engine System
In order for us better understand result integration strategies, we need to take a look the science involved in creating a MSE. These can also be considered strategies which help the MSE return better search results. There are three components to take into consideration when building a MSE these include search engine selection,result extraction and result integration.
2.1 Search Engine Selection
In order for the MSE to chose which search e...

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...sadvantage is if a user is English speaking and searches for the a hotel in China the resulting pages may be in a di erent language possibly Mandarin of domain name .cn. This method is highly personalised to queries of a geographical nature as compared to the other methods described above.

Works Cited

Leonidas Akritidis, Dimitrios Katsaros, and Panayiotis Bozanis. E ective ranking fusion methods for personalized metasearch engines.
Javed A. Aslam and Mark Montague. Models for metasearch.
Hossein Jadidoleslamy. Search result merging and ranking strategies in meta-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 WISE
Conference, pages 53{66, 2005.
M. Elena Renda and Umberto Straccia. Web metasearch: Rank vs. score based rank aggregation methods, 2003.

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