Department of Computer Science

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A survey on search results diversification techniques
(Neural Comput & Applic, 2015) Adnan Abid; Naveed Hussain; Kamran Abid; Farooq Ahmad; Muhammad Shoaib Farooq; Uzma Farooq; Sher Afzal Khan; Yaser Daanial Khan; Muhammad Azhar Naeem; Nabeel Sabir
The quantity of information placed on the web has been greater than before and is increasing rapidly day by day. Searching through the huge amount of data and finding the most relevant and useful result set involves searching, ranking, and presenting the results. Most of the users probe into the top few results and neglect the rest. In order to increase user’s satisfaction, the presented result set should not only be relevant to the search topic, but should also present a variety of perspectives, that is, the results should be different from one another. The effectiveness of web search and the satisfaction of users can be enhanced through providing various results of a search query in a certain order of relevance and concern. The technique used to avoid presenting similar, though relevant, results to the user is known as a diversification of search results. This article presents a survey of the approaches used for search result diversification. To this end, this article not only provides a technical survey of existing diversification techniques, but also presents a taxonomy of diversification algorithms with respect to the types of search queries.