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    STUDIA INFORMATICA - Issue no. 2 / 2014  
         
  Article:   FINDING, MANAGING AND ENFORCING CFDS AND ARS VIA A SEMI-AUTOMATIC LEARNING STRATEGY.

Authors:  . 		 
       
         
  Abstract:   This paper describes our strategy, which fi nds Conditional Functional Dependencies (CFDs) and Association Rules (ARs), and instead of using them to clean dirty data we use them to prevent their appearance in the database. We achieve this by di fferentiating strict CFDs/ARs from apparent CFDs/ARs. If we know about a CFD/AR that it will be valid in the future, we can rely on them by creating constraints which guarantee that the CFD-rule will not be breached by insertions or modi fications. Along with complete management of CFDs/ARs our implemented application called DependencyManager also uses Formal Concept Analysis(FCA) methods to analyze the strict CFDs/ARs and draw useful conclusions, helping the users of the application to prevent inconsistencies, fix bugs and optimize their queries and applications by providing a lattice ofCFDs/ARs, using usefulness as the relation.

2010 Mathematics Subject Classi fication. 68P15.1998 CR Categories and Descriptors. H.2.8 [Database Management]: Database Applications- Data mining.

Key words and phrases. Dependency Mining, Conditional Functional Dependency, FormalConcept Analysis, Association Rules.
 
         
     
         
         
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