Evaluation of web search engine based on ranking of results and its features
Rakesh Chandra Balabantaray
Abstract
Rakesh Chandra Balabantaray
Abstract
Search engines help the user to surf the web. Due to the vast number of web pages, it is highly impossible for the user to retrieve the appropriate web page he needs. Thus, web search ranking algorithms play an important role in ranking web pages, so that the user could retrieve the page which is most relevant to the user's query. Measuring the information retrieval effectiveness of World Wide Web search engines is costly because of human relevance judgements involved. However, both for business enterprises and people it is important to know the most effective web search engines, since such search engines help their users find higher number of relevant web pages with less effort. Furthermore, this information can be used for several practical purposes. This paper presents a study of the applicability of two user-effort-sensitive evaluation measures on five web search engines (Google, Ask, Yahoo, AOL and Bing). Twenty queries were collected from the list of most hit queries in the last year from various search engines and based upon that search engines are evaluated.
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Search engines help the user to surf the web. Due to the vast number of web pages, it is highly impossible for the user to retrieve the appropriate web page he needs. Thus, web search ranking algorithms play an important role in ranking web pages, so that the user could retrieve the page which is most relevant to the user's query. Measuring the information retrieval effectiveness of World Wide Web search engines is costly because of human relevance judgements involved. However, both for business enterprises and people it is important to know the most effective web search engines, since such search engines help their users find higher number of relevant web pages with less effort. Furthermore, this information can be used for several practical purposes. This paper presents a study of the applicability of two user-effort-sensitive evaluation measures on five web search engines (Google, Ask, Yahoo, AOL and Bing). Twenty queries were collected from the list of most hit queries in the last year from various search engines and based upon that search engines are evaluated.
Key concepts: Computer science, Information retrieval, Ranking (information retrieval), Search engine, Spamdexing, World Wide Web, Web crawler, Web search query