| A SQL database system for solving constraints |
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Conference on Information and Knowledge Management
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Proceeding of the 2nd PhD workshop on Information and knowledge management
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Napa Valley, California, USA
SESSION: Session 1
table of contents
Pages 1-8
Year of Publication: 2008
ISBN:978-1-60558-257-3
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Downloads (6 Weeks): 15, Downloads (12 Months): 98, Citation Count: 0
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ABSTRACT
It has long been recognized that practical contexts for constraint satisfaction problems (CSP) often involve large relational databases (RDB). Early attempts to marry constraint solving systems and relational database systems include deductive and constraint databases that reuse important ideas from logic programming. These techniques required knowledge outside the scope of traditional database users. The recent proposal by Cadoli and Mancini, "consql", shows that a simple extension to SQL provides a viable basis for modeling CSP. This opens the possibility for transparently integrating CSP with databases using SQL - the most widely known and popular database language. Such an extension brings the power of constraint problem solving to SQL knowledgeable users. Towards that end, the current research describes a case study in the engineering details of designing and implementing such a prototype. The SQL-based constraint data engine (SCDE) supports key concepts of "consql", with several new syntax to better align the administration of CSP related notions with ordinary SQL. SCDE manages the internal representation and solving of constraints through a combination of ordinary SQL and a satisfiability solver, SATO. Initial performance tests on the 1997-98 ACC Basketball Scheduling problem shows the feasibility and potential of the SCDE design. Ongoing and future work include completing a programming environment for end-users to specify, test and debug constraint problem specification; combining the database engine with a more interactive version of SATO to support objective functions, and automatic problem analysis and decomposition for improving the performance of hard constraint problems.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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