We present a new application for keyword search within relational databases, which uses a novel algorithm to solve the join discovery problem by finding Memex-like trails through the graph of foreign key dependencies. It differs from previous efforts in the algorithms used, in the presentation mechanism and in the use of primary-key only database queries at query-time to maintain a fast response for users. We present examples using the DBLP data set.
The join discovery problem is related to the problem tackled by the @cite_18 @cite_11 . The idea underlying the universal relation model is to allow querying the database soley through its attributes without explicitly specifying the join paths. The expressive querying power of such a system is essentially that of a union of conjunctive queries (see @cite_19 ). DbSurfer takes this approach further by allowing the user to specify values (keywords) without stating their related attributes and providing relevance based filtering.
@cite_19 @cite_18 @cite_11
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The representative instance is proposed as a representation of the data stored in a database whose relations are not the projections of a universal instance. Database schemes are characterized for which local consistency implies global consistency. (Local consistency means that each relation satisfies its own functional dependencies; global consistency means that the representative instance satisfies all the functional dependencies.) A method of efficiently computing projections of the representative instance is given, provided that local consistency implies global consistency. Throughout, it is assumed that a cover of the functional dependencies is embodied in the database scheme in the form of keys. This book goes into the details of database conception and use, it tells you everything on relational databases. from theory to the actual used algorithms.