Robust Approach For Query Grouping Using User Search Logs

Users are increasingly pursuing complex task-oriented goals on the Web, such as making travel arrangements, managing finances or planning purchases. To better support users in their long-term information quests on the Web, search engines keep track of their queries and clicks while searching online. The project study the problem of organizing a user’s historical queries into groups in a dynamic and automated fashion. Automatically identifying query groups is helpful for a number of different search engine components and applications, such as query suggestions, result ranking, query alterations, sessionization, and collaborative search. Propose a more robust approach that leverages search query logs.