Keyword search over entity databases (e.g., product, movie
\ndatabases) is an important problem. Current techniques for
\nkeyword search on databases may often return incomplete
\nand imprecise results. On the one hand, they either require
\nthat relevant entities contain all (or most) of the query keywords,
\nor that relevant entities and the query keywords occur
\ntogether in several documents from a known collection.
\nNeither of these requirements may be satisfied for a number
\nof user queries. Hence results for such queries are likely to
\nbe incomplete in that highly relevant entities may not be returned.
\nOn the other hand, although some returned entities
\ncontain all (or most) of the query keywords, the intention
\nof the keywords in the query could be different from that in
\nthe entities. Therefore, the results could also be imprecise.
\nTo remedy this problem, in this paper, we propose a general
\nframework that can improve an existing search interface
\nby translating a keyword query to a structured query.
\nSpecifically, we leverage the keyword to attribute value associations
\ndiscovered in the results returned by the original
\nsearch interface. We show empirically that the translated
\nstructured queries alleviate the above problems.<\/p>\n","protected":false},"excerpt":{"rendered":"
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 […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13563],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-163642","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-data-platform-analytics","msr-locale-en_us"],"msr_publishername":"","msr_edition":"Proceedings of International Conference on Very Large Databases 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