Negative associacion rules – computing, measures and application areas

Anna Kotulla


This article presents positive and negative association rules. The most important measures for association rules are described. A sample analysis was done using the R environment. Classification based on positive and negative association rules was described.


data analysis; data mining; affinity analysis; positive association rules; negative association rules

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Antonie M.-L., Zaïane O. R.: An Associative Classifier based on Positive and Negative Rules. 9th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery, Paryż 2004.

Agrawal R., Imielinski T., Swami A.: Mining Association Rules between Sets of Items in Large Databases. SIGMOD Conference Washington, D.C. 1993, s. 207÷216.

Agrawal R., Srikant R.: Fast Algorithms for Mining Association Rules. VLDB Conference, Santiago de Chile 1994, s. 487÷499.

Brin S., Motwani R., Ullman J. D., Tsur S.: Dynamic Itemset Counting and Implication Rules for Market Basket Data. ACM SIGMOD International Conference on Management of Data, Tucson, Arizona, USA 1997, s. 255÷264.

Ghaderi R., Minaei-Bidgoli B.: Detecting Data Errors with Employing Negative Association Rules. International Journal of Digital Content Technology and its Applications, Vol. 3, No. 3, 2009, s. 91÷95.

Han J., Kamber M.: Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers, San Francisco 2006.

Han J., Pei J., Yin Y., Mao R.: Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach. Data Mining and Knowledge Discovery, Kluwer Academic Publishers Hingham, MA 2004.

Hahsler M., Buchta Ch., Gruen B., Hornik K.: arules: Mining Association Rules and Frequent Itemsets. Manual, (sprawdzono 12.01.2012).

Hahsler M., Gruen B., Hornik K.: arules - A Computational Environment for Mining, Association Rules and Frequent Item Sets. Journal of Statistical Software, Vol. 14, No.15, 2005, s. 1÷25.

Kavitha Rani B., Srinivas K., Ramasubbareddy B., Govardhan A.: Mining Negative Association Rules. International Journal of Engineering and Technology, Vol. 3(2), 2011, s. 100÷105.

Markov Z., Larose D. T.: Eksploracja zasobów internetowych. Wydawnictwo Naukowe PWN, Warszawa 2009.

Ramasubbareddy B., Govardhan A., Ramamohanreddy A.: Classification Based on Positive and Negative Association Rules. International Journal of Data Engineering, Vol. 2, 2011.

Tan P.-N., Steinbach M., Kumar V.: Introduction to Data Mining. Addison-Wesley, 2005.

Thabtah F., Cowling P., Peng Y.: MMAC: A New Multi-class, Multi-label Associative Classification Approach. 4th IEEE International Conference on Data Mining, Brighton UK 2004, s. 217÷224.

Thabtah F., Cowling P., Peng Y.: MCAR: Multi-class Classification Based on Association Rule Approach. 3rd IEEE International Conference on Computer Systems and Applications, Kair 2005, s. 1÷7.

Wu X., Zhang Ch., Zhang Sh.: Efficient Mining of Both Positive and Negative Association Rules. ACM Transactions on Information Systems, Vol. 22, No. 3, 2004, s. 381÷405.

The R Foundation for Statistical Computing: The R Project for Statistical Computing, (sprawdzono 12.01.2012).