A simple greedy algorithm for finding functional relations: efficient implementation and average case analysis

Authors:
Tatsuya Akutsu;Satoru Miyano;Satoru Kuhara
Affiliations:
Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji-city, Kyoto 611-0011, Japan and Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokan ...;Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan;Graduate School of Genetic Resources Technology, Kyushu University, Hakozaki 6-10-1, Higashi-ku, Fukuoka 812-8581, Japan
Venue:
Theoretical Computer Science
Year:
2003

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Abstract

Inferring functional relations from relational databases is important for the discovery of scientific knowledge because many experimental data are represented in the form of tables and many rules are represented in the form of functions. A simple greedy algorithm has been known as an approximation algorithm for this problem. This paper presents an efficient implementation of the algorithm. This paper also shows that the algorithm can identify an exact solution for simple functions if input data for each function are generated uniformly at random and the size of the domain is bounded by a constant. Results of computational experiments using artificially generated data are presented to verify the approach.