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

Keyword search over entity databases (e.g., product, movie
databases) is an important problem. Current techniques for
keyword search on databases may often return incomplete
and imprecise results. On the one hand, they either require
that relevant entities contain all (or most) of the query keywords,
or that relevant entities and the query keywords occur
together in several documents from a known collection.
Neither of these requirements may be satisfied for a number
of user queries. Hence results for such queries are likely to
be incomplete in that highly relevant entities may not be returned.
On the other hand, although some returned entities
contain all (or most) of the query keywords, the intention
of 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 general
framework that can improve an existing search interface
by translating a keyword query to a structured query.
Specifically, we leverage the keyword to attribute value associations
discovered in the results returned by the original
search interface. We show empirically that the translated
structured queries alleviate the above problems.