Detailed Investigation on Strategies Developed for Effective Discovery of Matching Dependencies

ABSTRACT: This paper details about various methods prevailing in literature for efficient discovery of matching dependencies. The concept of matching dependencies (MDs) has recently been proposed for specifying matching rules for object identification. Similar to the functional dependencies with conditions, MDs can also be applied to various data quality applications such as detecting the violations of integrity constraints. The problem of discovering similarity constraints for matching dependencies from a given database instance is taken into consideration. This survey would promote a lot of research in the area of information mining

Efficient Search for Strong Partial Determinations

Our work offers both a solution to the problem of finding functional dependencies that are distorted by noise and to the open problem of efficiently finding strong (i.e., highly compressive) partial determinations per se. Briefly, we introduce a restricted form of search for partial determinations which is based on functional dependencies. Focusing attention on solely partial determinations derivable from overfitting functional dependencies enables efficient search for strong partial determinations. Furthermore, we generalize the compression-based measure for evaluating partial determinations to n-valued attributes. Applications to real-world data suggest that the restricted search indeed retrieves a subset of strong partial determinations in much shorter runtimes, thus showing the feasibility and usefulness of our approach. 1 Introduction Functional dependencies [Mannila & Raiha, 1994] are a fundamental form of knowledge to be discovered in databases. In real-world databases, however..