Keyword++: A Framework to Improve Keyword Search Over Entity Databases

Keyword search over entity databases (e.g., product, moviedatabases) is an important problem. Current techniques forkeyword search on databases may often return incompleteand imprecise results. On the one hand, they either requirethat relevant entities contain all (or most) of the query key-words, or that relevant entities and the query keywords oc-cur together in several documents from a known collection.Neither of these requirements may be satisfied for a numberof user queries. Hence results for such queries are likely tobe incomplete in that highly relevant entities may not be re-turned. On the other hand, although some returned entitiescontain all (or most) of the query keywords, the intentionof the keywords in the query could be different from that in the entities. Therefore, the results could also be imprecise.To remedy this problem, in this paper, we propose a gen-eral framework that can improve an existing search inter-face by translating a keyword query to a structured query.Specifically, we leverage the keyword to attribute value as-sociations discovered in the results returned by the originalsearch interface. We show empirically that the translatedstructured queries alleviate the above problems.