Data processing: database and file management or data structures – Database and file access – Preparing data for information retrieval
Reexamination Certificate
2008-02-21
2010-10-19
Mofiz, Apu M. (Department: 2161)
Data processing: database and file management or data structures
Database and file access
Preparing data for information retrieval
C707S737000, C707S736000, C707S802000, C707S803000
Reexamination Certificate
active
07818323
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. The representative finder also arranges the representative tables by topic as a topical directory and outputs the topical directory.
REFERENCES:
patent: 5875446 (1999-02-01), Brown et al.
patent: 7246136 (2007-07-01), Cameron et al.
patent: 2003/0220913 (2003-11-01), Doganata et al.
patent: 2006/0161517 (2006-07-01), Bhattacharjee et al.
patent: 2008/0005137 (2008-01-01), Surendran et al.
patent: 2008/0228745 (2008-09-01), Markus et al.
patent: 2009/0055368 (2009-02-01), Rewari et al.
Wu Wensheng, et al., “Discovering Topical Structures of Databases” Jun. 12, 2008, SIGMOD '08 ACM, p. 1019-1030.
Ralitsa Angelova, et al., “Graph-based Text Classification: Learn from Your Neighbors,” Dynamically Evolving , Large Scale Information Systems, 2006, pp. 485-492.
Ralitsa Angelova, et al., “A Neighborhood-Based Approach for Clustering of Linked Document Collections,” MPI-I-2006-5-005, Aug. 2006.
Kulis, B., et al., “Semi-supervised Graph Clustering: A Kernel Approach,”Proceedings of the 22nd International Conference on Machine Learning, Bonn, Germany, pp. 457-464, Aug. 2005.
Manjrekar Rajesh P.
Reinwald Berthold
Sismanis John
Wu Wensheng
Gibb I.P. Law Firm LLC
International Business Machines - Corporation
Mofiz Apu M.
Stace Brent
LandOfFree
Discovering topical structures of databases does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Discovering topical structures of databases, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Discovering topical structures of databases will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-4155634