Peculiarity Oriented Mining and Its Application for Knowledge Discovery in Amino-Acid Data

The paper proposes a way of peculiarity oriented mining and its application for knowledge discovery in the amino-acid data set. We introduce the peculiarity rules as a new type of association rules, which can be discovered from a relatively small number of peculiar data by searching the relevance among the peculiar data. We argue that the peculiarity rules represent a typically unexpected, interesting regularity hidden in the amino-acid data set.

[1]  Tomasz Imielinski,et al.  Database Mining: A Performance Perspective , 1993, IEEE Trans. Knowl. Data Eng..

[2]  Jan Komorowski,et al.  Principles of Data Mining and Knowledge Discovery , 2001, Lecture Notes in Computer Science.

[3]  Alex Alves Freitas,et al.  On Objective Measures of Rule Surprisingness , 1998, PKDD.

[4]  Lotfi A. Zadeh,et al.  Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic , 1997, Fuzzy Sets Syst..

[5]  Heikki Mannila,et al.  Fast Discovery of Association Rules , 1996, Advances in Knowledge Discovery and Data Mining.

[6]  Sadaaki Miyamoto,et al.  Rough Sets and Current Trends in Computing , 2012, Lecture Notes in Computer Science.

[7]  Einoshin Suzuki,et al.  Autonomous Discovery of Reliable Exception Rules , 1997, KDD.

[8]  Abraham Silberschatz,et al.  What Makes Patterns Interesting in Knowledge Discovery Systems , 1996, IEEE Trans. Knowl. Data Eng..

[9]  Tsau Young Lin,et al.  Frameworks for Mining Binary Relations in Data , 1998, Rough Sets and Current Trends in Computing.

[10]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[11]  Wynne Hsu,et al.  Using General Impressions to Analyze Discovered Classification Rules , 1997, KDD.

[12]  Yiyu Yao,et al.  Peculiarity Oriented Multi-database Mining , 1999, PKDD.

[13]  Yiyu Yao.  Granular Computing using Neighborhood Systems , 1999 .

[14]  Andrzej Skowron,et al.  New Directions in Rough Sets, Data Mining, and Granular-Soft Computing , 1999, Lecture Notes in Computer Science.

[15]  Stefan Wrobel,et al.  An Algorithm for Multi-relational Discovery of Subgroups , 1997, PKDD.

[16]  Christos Faloutsos,et al.  Automated Learning and Discovery State-of-the-Art and Research Topics in a Rapidly Growing Field , 1999, AI Mag..