Performance Comparative Analysis of Web Search Engines for Retrieving Computer Science Research Articles Using Information Retrieval Approaches

Abstract

The Web has been proved as the global information source containing billions of accessible resources (e.g., web pages, documents, images, videos, etc.) pertaining information about different topics. The Web is growing exponentially, resulting into information overload problem. Therefore, finding and retrieving relevant information on the Web is troublesome for the users. The web search engines are developed to help users in searching and retrieving information on the Web. However, the enlarged list of web search engines and lack of availability of their performances information makes web search engine selection difficult for the computer science research scholars to retrieve relevant research articles quickly and precisely.  This paper presents comparative analysis of top five web search engines (i.e., Google, Bing, Yahoo, Baidu and Yandex) to retrieve computer science research articles in response to domain-specific queries varying in complexity. The comparison and evaluation methodology, performance analysis using information retrieval metrics (i.e., response time, recall, and precision), and systematic comparison of the results to illustrate strength and weakness of the web search engines is presented. It is found that Google is the performance-wise best web search engine with lowest response time, high recall, and high precision. However, the Baidu has shown overall worst performance. The findings could be helpful for computer science research scholars in selecting and using appropriate web search engine in their searching processes.