Acquisition of Fuzzy Association Rules from Medical Data

Association rules are one of the best studied models for knowledge acquisition in the field of Data Mining. Many papers regarding algorithms, measures and related problems can be found in the literature. A brief summary of the main works (to our knowledge) in this area can be found in the references of this paper.

[1]  Alan L. Cox,et al.  Efficient mining for association rules with relational database systems , 1999, Proceedings. IDEAS'99. International Database Engineering and Applications Symposium (Cat. No.PR00265).

[2]  Man Hon Wong,et al.  Mining fuzzy association rules in databases , 1998, SGMD.

[3]  Tomasz Imielinski,et al.  Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.

[4]  L. Zadeh.  A COMPUTATIONAL APPROACH TO FUZZY QUANTIFIERS IN NATURAL LANGUAGES , 1983 .

[5]  Arbee L. P. Chen,et al.  The analysis of relationships in databases for rule derivation , 2004, Journal of Intelligent Information Systems.

[6]  Rajeev Motwani,et al.  Dynamic itemset counting and implication rules for market basket data , 1997, SIGMOD '97.

[7]  Srinivasan Parthasarathy,et al.  New Algorithms for Fast Discovery of Association Rules , 1997, KDD.

[8]  Marek Wojciechowski,et al.  Itemset Materializing for Fast Mining of Association Rules , 1998, ADBIS.

[9]  Daniel Sánchez,et al.  Fuzzy cardinality based evaluation of quantified sentences , 2000, Int. J. Approx. Reason..

[10]  Keith C. C. Chan,et al.  An effective algorithm for discovering fuzzy rules in relational databases , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[11]  Heikki Mannila,et al.  Efficient Algorithms for Discovering Association Rules , 1994, KDD Workshop.

[12]  M.A.W. Houtsma,et al.  Set-Oriented Mining for Association Rules , 1993, ICDE 1993.

[13]  Daniel A. Keim,et al.  On Knowledge Discovery and Data Mining , 1997 .

[14]  Ramakrishnan Srikant,et al.  Fast algorithms for mining association rules , 1998, VLDB 1998.

[15]  Arun N. Swami,et al.  Set-oriented mining for association rules in relational databases , 1995, Proceedings of the Eleventh International Conference on Data Engineering.

[16]  Nie Yong.  Mining quantitative association rules , 2000 .

[17]  D. S. Fernández.  Adquisición de relaciones entre atributos en bases de datos relacionales , 2000 .

[18]  Li Shen,et al.  New Algorithms for Efficient Mining of Association Rules , 1999, Inf. Sci..

[19]  Shamkant B. Navathe,et al.  An Efficient Algorithm for Mining Association Rules in Large Databases , 1995, VLDB.

[20]  David Maier,et al.  The Theory of Relational Databases , 1983 .

[21]  Arbee L. P. Chen,et al.  Efficient Graph-Based Algorithm for Discovering and Maintaining Knowledge in Large Databases , 1999, PAKDD.

[22]  Yungho Leu,et al.  An effective Boolean algorithm for mining association rules in large databases , 1999, Proceedings. 6th International Conference on Advanced Systems for Advanced Applications.

[23]  Philip S. Yu,et al.  An effective hash-based algorithm for mining association rules , 1995, SIGMOD '95.

[24]  Nicolas Pasquier,et al.  Efficient Mining of Association Rules Using Closed Itemset Lattices , 1999, Inf. Syst..

[25]  Robert Meersman,et al.  On the Complexity of Mining Quantitative Association Rules , 1998, Data Mining and Knowledge Discovery.

[26]  Edward H. Shortliffe,et al.  A model of inexact reasoning in medicine , 1990 .

[27]  Renée J. Miller,et al.  Association rules over interval data , 1997, SIGMOD '97.

[28]  Rajeev Motwani,et al.  Beyond Market Baskets: Generalizing Association Rules to Dependence Rules , 1998, Data Mining and Knowledge Discovery.

[29]  Ramakrishnan Srikant,et al.  Mining quantitative association rules in large relational tables , 1996, SIGMOD '96.