PERFORMING SEARCH QUERY DIMENSIONAL ANALYSIS ON HETEROGENEOUS STRUCTURED DATA BASED ON RELATIVE DENSITY

摘要

A method is provided for responding to user search requests with suggested categories and attributes that have a high probability of being useful to the user for refining the search. The method is described in the context of a shared search engine platform in which multiple vertical domain repositories reside. The common search engine can search all of the repositories in a single search. The multiple vertical domain repositories can be heterogeneous in type, size, and semantics. Choosing search hints in the face of such diversity of content can be a challenge. The approach uses a “relative density” measure to determine which categories and attributes to recommend and overcomes the problem of repositories with more content dominating the chosen search terms that are returned to the user.