Improving faceted search results for web-based information exploration

Abstract

The World Wide Web (WWW), a fast-growing store, contains a significant portion of human knowledge. However, the sheer scale of the Web, along with the fact that it is decentralized, highly redundant, and largely inaccurate, causes the use of the knowledge is quite cumbersome. The present search engines (SEs) use the query, and the response lookup process is incapable of producing a precise result. Thus, researchers work beyond this paradigm to explore a new class of methods to seek information, which known as an exploratory search (ES). This ES is open-ended, and its faceted search (FS) improves the overall search process. The search engine presented in this study is running in the cloud computing platform environment. Its development is based on the idea of improving visual ES while exploring information on the Web. This notion reflects the process of seeking and combing the vast information by using the coordinated visualization method, apart from minimizing the effort spent in seeking information per query. Finally, we evaluate the proposed prototype against the Internet Movie Database (IMDb) search engine, an online database of information related to films, television programs, home videos, video games, and streaming content online including cast, production crew, and personal biographies, plot summaries, trivia, fan, and critical reviews, and ratings. The results show that the proposed search engine gives more relevant search results as compared with the others. © 2020, Insight Society.