Date Added: Apr 2011
Query recommendation is an invaluable tool for enabling users to speed up their searches. In this paper, the authors present algorithms for generating query suggestions, assuming no previous knowledge of the collection. They developed an online OLAP algorithm to generate query suggestions for the users based on the frequency of the keywords in the selected documents and the correlation between the keywords in the collection. In addition, performance and scalability experiments of these algorithms are presented as proof of their feasibility. They also present sampling as an additional approach for improving performance by using approximate results.