Abstract: A system and method for automatically discovering topical structures of databases includes a model builder adapted to compute various kinds of representations for the database based on schema information and data values of the database. A plurality of base clusterers is also provided, one for each representation. Each base clusterer is adapted to perform, for the representation, preliminary topical clustering of tables within the database to produce a plurality of clusters, such that each of the clusters corresponds to a set of tables on the same topic. A meta-clusterer aggregates results of the clusterers into a final clustering, such that the final clustering comprises a plurality of the clusters. A representative finder identifies representative tables from the clusters in the final clustering. The representative finder identifies at least one representative table for each of the clusters in the final clustering.

Abstract: A system and method for automatically discovering topical structures of databases includes a model builder adapted to compute various kinds of representations for the database based on schema information and data values of the database. A plurality of base clusterers is also provided, one for each representation. Each base clusterer is adapted to perform, for the representation, preliminary topical clustering of tables within the database to produce a plurality of clusters, such that each of the clusters corresponds to a set of tables on the same topic. A meta-clusterer aggregates results of the clusterers into a final clustering, such that the final clustering comprises a plurality of the clusters. A representative finder identifies representative tables from the clusters in the final clustering. The representative finder identifies at least one representative table for each of the clusters in the final clustering.