Collaborative Querying for Enhanced Information Retrieval

Communication and collaboration with other people is a major theme in the information seeking process. Collaborative querying addresses this issue by sharing other users’ search experiences to help users formulate appropriate queries to a search engine. This paper describes a collaborative querying system that helps users with query formulation by finding previously submitted similar queries through mining web logs. The system operates by clustering and recommending related queries to users using a hybrid query similarity identification approach. The system employs a graph-based approach to visualize the query recommendations.