Semantic path ranking scheme for relational keyword queries

Existing works on keyword search over relational databases typically do not consider users' search intention for a query and return many answers which often overwhelm users. We observe that a database is in fact a repository of real world objects that interact with each other via relationships. In this work, we identify four types of semantic paths between objects and design an algorithm called pathRank to compute and rank the results of keyword queries. The answers are grouped by the types of semantic paths which reflect diff erent query interpretations, and are annotated to facilitate user understanding.