International Business Machines Corporation
Dynamic faceting for personalized search and discovery

Abstract:

Methods, computer program products, and systems are presented. The methods include, for instance: determining user clusters and navigation-type clusters based on multiple information requests, and training facets and corresponding usefulness factor of the facets from the multiple information requests by machine learning. When a user submits a query, the user and the query is respectively mapped with one of the user clusters and the navigation-type clusters, and the query is customized based on the associated pair of clusters. Results of the query are obtained, ranked by usefulness of the facets as determined according to the pair of clusters, and presented to the user.