Integration Stategies of Meta Search Engines Essays

Integration Stategies of Meta Search Engines Essays

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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...


... middle of paper ...


...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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