Utilising Creative Computing and data mining techniques to analyse queries in a meta-search system
Sicong Ma, Siyan Li, Hongji Yang
Abstract
Sicong Ma, Siyan Li, Hongji Yang
Abstract
As the World Wide Web has a huge number of information and update rapidly, the needs of people for searching information from the web increase dramatically. Meanwhile, most of current search engines can search a query from websites, but cannot present the most relevant results to users. The main challenge for search engines and meta search engines are how to describe and analyse a query more comprehensively. In order to solve this problem, this paper presents a meta-search engine named Personlised Meta Search Engine (PMSE) that has been used to adapt the web search processes to meet users' requirement. Firstly, a technique will enrich the given query by data mining and creative computing. Secondly, a new meta-search engine is developed to make the results more relevant. Finally, an example is used to demonstrate what the proposed approach will be described more comprehensively and to produce fewer but more precise answers to individual users.
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As the World Wide Web has a huge number of information and update rapidly, the needs of people for searching information from the web increase dramatically. Meanwhile, most of current search engines can search a query from websites, but cannot present the most relevant results to users. The main challenge for search engines and meta search engines are how to describe and analyse a query more comprehensively. In order to solve this problem, this paper presents a meta-search engine named Personlised Meta Search Engine (PMSE) that has been used to adapt the web search processes to meet users' requirement. Firstly, a technique will enrich the given query by data mining and creative computing. Secondly, a new meta-search engine is developed to make the results more relevant. Finally, an example is used to demonstrate what the proposed approach will be described more comprehensively and to produce fewer but more precise answers to individual users.
Key concepts: Computer science, Search engine, Metasearch engine, Web search query, Search analytics, Information retrieval, Web query classification, Search-oriented architecture