2015•Unpublished venueRequires access

A heuristic approach for search engine selection in meta-search engine

Rajesh Kumar Dhanaraj, Sunil Kumar Singh, Virendra Kumar

Open publisher page 8 citations

Abstract

The web becomes a huge resource of information. The people all over the world use the web on a regular basis and the number of users is increasing rapidly. Whenever a user needs to retrieve the information on the web, the information need of the user is stored in databases of the different underlying search engine. It is very challenging task to identify most relevant underlying search engine that is likely to be contain the useful information for a user query. In this paper, we proposed an algorithm to select the appropriate search engine in meta-search engine for the user query using genetic algorithm and compare with existing algorithm. The objective of search engine selection is to improve the efficiency as it would result in sending a query to only potentially useful underlying search engine.

About this research paper

What this paper is about

The web becomes a huge resource of information. The people all over the world use the web on a regular basis and the number of users is increasing rapidly. Whenever a user needs to retrieve the information on the web, the information need of the user is stored in databases of the different underlying search engine. It is very challenging task to identify most relevant underlying search engine that is likely to be contain the useful information for a user query. In this paper, we proposed an algorithm to select the appropriate search engine in meta-search engine for the user query using genetic algorithm and compare with existing algorithm. The objective of search engine selection is to improve the efficiency as it would result in sending a query to only potentially useful underlying search engine.

Why it matters

OpenAlex reports 8 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

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Method / approach

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Available abstract

The web becomes a huge resource of information. The people all over the world use the web on a regular basis and the number of users is increasing rapidly. Whenever a user needs to retrieve the information on the web, the information need of the user is stored in databases of the different underlying search engine. It is very challenging task to identify most relevant underlying search engine that is likely to be contain the useful information for a user query. In this paper, we proposed an algorithm to select the appropriate search engine in meta-search engine for the user query using genetic algorithm and compare with existing algorithm. The objective of search engine selection is to improve the efficiency as it would result in sending a query to only potentially useful underlying search engine.

Key concepts: Metasearch engine, Computer science, Search analytics, Search engine, Search-oriented architecture, Information retrieval, Web search query, Spamdexing

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