Take a look at the new version of this page: [ beta version ]. Tell us what you think.

ABSTRACT

Large collections of documents are commonly created around a database, where a typical database schema may contain hundreds of tables and thousands of columns. We developed a system based on SQL code generation and User-Defined Functions that analyzes document-to-metadata links by extracting a basic set of relationships at different levels of granularities: coarse, medium and fine. Such relationships are then stored and queried in the DBMS, allowing the user to explore, query, and rank how columns and tables are related to users and applications. At the same time, our system provides typical information retrieval capabilities for querying medium-sized document collections of interrelated documents in the DBMS, with an acceptable performance.

REFERENCES

• 1: Carlos Garcia-Alvarado , Carlos Ordonez, Information retrieval from digital libraries in SQL, Proceeding of the 10th ACM workshop on Web information and data management, October 30-30, 2008, Napa Valley, California, USA [doi>10.1145/1458502.1458512]
• 2: Ihab F. Ilyas , George Beskales , Mohamed A. Soliman, A survey of top-k query processing techniques in relational database systems, ACM Computing Surveys (CSUR), v.40 n.4, p.1-58, October 2008 [doi>10.1145/1391729.1391730]
• 3: Carlos Ordonez , Zhibo Chen , Javier García-García, Metadata management for federated databases, Proceedings of the ACM first workshop on CyberInfrastructure: information management in eScience, November 09-09, 2007, Lisbon, Portugal [doi>10.1145/1317353.1317361]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.7 Database Administration
          Subjects: Data warehouse and repository

General Terms:
Design, Documentation, Management