Web search engines have stored in their logs information about users since they started to operate. This information often serves many purposes. The primary focus of this survey is on introducing to the discipline of query mining by showing its foundations and by analyzing the basic algorithms and techniques that are used to extract useful knowledge from this (potentially) infinite source of information. We show how search applications may benefit from this kind of analysis by analyzing popular applications of query log mining and their influence on user experience. We conclude the paper by, briefly, presenting some of the most challenging current open problems in this field.
Web search engines have stored information about users in their logs since they started to operate. This information often serves many purposes. Mining Query Logs: Turning Search Usage Data into Knowledge reviews some of the most recent techniques dealing with query logs and how they can be used to enhance web search engine operations. It summarizes the basic results concerning query logs: analyses, techniques used to extract knowledge, most remarkable results, most useful applications, and open issues and possibilities that remain to be studied. It reviews fundamental and state-of-the-art techniques. In each section, even if not directly specified, it reviews and analyzes the algorithms used, and not just their results. Mining Query Logs: Turning Search Usage Data into Knowledge is dedicated to those who want to know more about how search engines are so good at "guessing" the right answers to their queries, and also how they can do so quickly