Log analysis and adaptive search

I attended an interesting talk by Udo Kruschwitz on Adaptive Intranet Search last night as part of the Enterprise Search London Meetup. Udo has built a search engine for the University of Essex and has been investigating how to help users to refine their query using techniques such as suggesting related terms (there’s a similar feature in Xapian called ‘top terms’ – here’s an example). As part of this he’s done a great deal of analysis of query and session logs, and is building up expertise on automatically maintained domain knowledge – moving away from the traditional model of manually maintained networks relating one word or phrase to another. For example, his system is learning automatically that when users type “map” into the search box, they really want to search for “campus map”. The number of documents in his test collection is small and the volume of searches is low; it will be interesting to see how these ideas scale to larger collections and groups of users.

The group was small, informal and seemed to consist mainly of those with expertise in implementing search solutions – no sales or marketing here, just a group of people discussing how best to get the job done.

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