DETECTING PRODUCT ATTRIBUTES ASSOCIATED WITH PRODUCT UPGRADES BASED ON BEHAVIORS OF USERS

摘要

A system may use search refinements to identify new product trends. These product trends may be associated with attributes or product features that may previously have been available, but are newly of interest to a users. The system may compare search refinements used by users during an earlier time period with search refinements used during a more recent time period to identify search refinements that are used more often during the later time period. Based on this comparison, the system can identify a product feature that is of interest to users during the later time period, but not the earlier time period. The system can then recommend products with the product feature to potential customers. Further, if the product feature was not available during the earlier time period, the system can identify to potential customers that the product feature is newly available in relation to the earlier time period.

主权项

1. An interactive computing system, comprising:
a server system that hosts an electronic catalog of items, the server system including a search engine that enables users to conduct searches of the electronic catalog using search queries, wherein the search engine includes a search refinement user interface that provides an option for a searcher to refine a search by selecting one or more item attributes from a listing of item attributes associated with the search, said listing based at least partly on an automated analysis of textual descriptions of items associated with the search; a data repository that stores search history data reflective of searches conducted by users via the search engine; an attribute trend engine that uses the search history data to identify item attributes used more frequently as search refinements during a second time period than during a first time period the precedes the second time period, the attribute trend engine thereby configured to identify search refinement trends reflective of increases in the availability or popularity of particular item attributes; and a recommendation engine that generates item recommendations for users based in part on the search refinement trends identified by the attribute trend engine.