Current approaches for answering queries with imprecise constraints require users to provide distance metrics and importance measures for attributes of interest. In this paper we focus on providing a domain and end-user independent solution for supporting imprecise queries over Web databases without affecting the underlying database. We propose a query processing framework that integrates techniques from IR and database research to efficiently determine answers for imprecise queries. We mine and use approximate functional dependencies between attributes to create precise queries having tuples relevant to the given imprecise query. An approach to automatically estimate the semantic distances between values of categorical attributes is also proposed. We provide preliminary results showing the utility of our approach.
Extracting information and insights from large databases is a time-consuming activity and has received considerable research attention recently. In this demo, we present DynaCet-a domain independent system that provides effective minimum-effort based dynamic faceted search solutions over enterprise databases. At every step, Dynacet suggests facets depending on the user response in the previous step. Facets are selected based on their ability to rapidly drill down to the most promising tuples, as well as on the ability of the user to provide desired values for them. The benefits provided include faster access to information stored in databases while taking into consideration the variance in user knowledge and preferences.
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