Toolbar navigation logs provide rich data for enhancing information discovery
on the Web. The value of this data resides in its scope, which goes beyond that
of traditional query-mining data sources, such as search-engine logs. In this
paper we present a methodology for extracting relevant association rules for
queries, based on historic user navigational data. In addition, we propose a
graph-based approach for extracting related queries and URLs for a given query.