1. A computer-implemented method comprising: under control of a computing device configured with specific computer-executable instructions: accessing, from an electronic data store, search history data for a plurality of users of an electronic catalog, said search history data comprising session query logs, each session query log including one or more query terms associated with a search request submitted by a respective user; analyzing the session query logs to generate one or more search session segments, each search session segment corresponding to a distinct search session and comprising one or more search requests; for each respective search session segment, generating one or more query pairs, each query pair comprising at least two query terms that are associated with the one or more search requests comprised in the respective search session segment; determining, for each respective query pair across all of the one or more search session segments, a query pair frequency indicative of how many times the respective query pair appears across all of the one or more search session segments; clustering the query pairs, based at least in part on the determined query pair frequencies, into a query cluster, said query cluster comprising two or more query terms determined to be highly correlated based at least in part on the clustering; accessing correlated attribute data, said correlated attribute data including two or more correlated attributes that tend to be correlated to each other; generating an item descriptor cluster comprising combinations of the two or more query terms and the two or more correlated attributes; generating, by executing a search request on the electronic catalog using the item descriptor cluster, an item cluster comprising items having at least one of the two or more correlated attributes; and providing an item recommendation for at least one item contained in the item cluster.