Users, Queries and Documents: A Unified Representation for Web Mining

The collective feedback of the users of an Information Retrieval system has been proved to be useful in many tasks. A popular approach in the literature is to process the logs stored by Internet Service Providers (ISP), Intranet proxies or Web search engines to extract a query-document bi-partite graph. In this paper, we propose to use a richer data structure which is able to preserve most of the information available in the logs including query refinements, page visits and search activity. In particular, we represent the query refinements as separate transitions between the corresponding query nodes in the graph and we augment the graph by associating one node to each single user. Users are linked to the queries which they have issued and to the documents they have visited. The resulting data structure is a complete representation of the collective search activity performed by the users of a search engine or of an Intranet. The experimental results show that this more powerful representation can be successfully used to improve the quality of query clustering and to discover query suggestions.