2016Indian Journal of Science and TechnologyOpen access

Behavior of Search Engines in Popular Queries

Siddharth Ghansela, Ashish Singh Negi

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Abstract

Objectives: Presently, various search engines are available in the web with huge database. Not only the available search engine but the query also plays important role for getting appropriate results from the search engines. Our objective is to show the importance of popular queries. Methods/Statistical Analysis: In this article, we have introduced two new categories of query the one is popular query and another one is non-popular query. We analyse the behaviour of search engines using popular queries in top three search engines and after that compared them with a traditional mathematical model for rank calculation along with user feedback method. Findings: By proposing new category of query we analyse how the behaviour of search engines changed. Here we are using three methods for calculating ranking in different types of search engines to give more strength to our results. Our findings are to show the importance of popular queries in different types of search engines. Application/Improvements: From this article, we conclude that the behaviour or search engine in popular query is different than a simple query; some of the search engine gives them more importance because of their popularities.Keywords: Behaviour, Popular, Query, Rank, Search Engine

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What this paper is about

Objectives: Presently, various search engines are available in the web with huge database. Not only the available search engine but the query also plays important role for getting appropriate results from the search engines. Our objective is to show the importance of popular queries. Methods/Statistical Analysis: In this article, we have introduced two new categories of query the one is popular query and another one is non-popular query. We analyse the behaviour of search engines using popular queries in top three search engines and after that compared them with a traditional mathematical model for rank calculation along with user feedback method. Findings: By proposing new category of query we analyse how the behaviour of search engines changed. Here we are using three methods for calculating ranking in different types of search engines to give more strength to our results. Our findings are to show the importance of popular queries in different types of search engines. Application/Improvements: From this article, we conclude that the behaviour or search engine in popular query is different than a simple query; some of the search engine gives them more importance because of their popularities.Keywords: Behaviour, Popular, Query, Rank, Search Engine

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Available abstract

Objectives: Presently, various search engines are available in the web with huge database. Not only the available search engine but the query also plays important role for getting appropriate results from the search engines. Our objective is to show the importance of popular queries. Methods/Statistical Analysis: In this article, we have introduced two new categories of query the one is popular query and another one is non-popular query. We analyse the behaviour of search engines using popular queries in top three search engines and after that compared them with a traditional mathematical model for rank calculation along with user feedback method. Findings: By proposing new category of query we analyse how the behaviour of search engines changed. Here we are using three methods for calculating ranking in different types of search engines to give more strength to our results. Our findings are to show the importance of popular queries in different types of search engines. Application/Improvements: From this article, we conclude that the behaviour or search engine in popular query is different than a simple query; some of the search engine gives them more importance because of their popularities.Keywords: Behaviour, Popular, Query, Rank, Search Engine

Key concepts: Search engine, Web search query, Computer science, Web query classification, Information retrieval, Ranking (information retrieval), Metasearch engine, Search-oriented architecture

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