A study of frequent itemset mining techniques

  • Authors

    • Sachin Sharma Manav Rachna International University, Faridabad
    • Shaveta Bhatia Manav Rachna International University, Faridabad
    2017-10-14
    https://doi.org/10.14419/ijet.v6i4.8300
  • Association Rules, Frequent Item Sets, Rare Item Sets, Support Threshold.

  • Abstract

    Frequent item set is the most crucial and expensive task for the industry today. It is the task of mining the information from different sources and a key approach in Data Mining. Frequent item sets satisfying the minimum threshold can be discovered. Association rules are extracted from frequent item sets. The Association rules are affected by the minimum support value entered by the user may be considered as Positive or negative. There may be some other Association rules, which involve the rare item sets. Various methods have been used by researchers for generating the Association Rules. In this paper, our aim is to study various techniques to generate the Association rules.

  • References

    1. [1] Arpan Shah et al. (2014),’A Collaborative Approach of Frequent Item Set Mining: A Survey’, International Journal of Computer Applications, Vol 107, No 8 https://doi.org/10.5120/18775-0088.

      [2] Agrawal, R. &Srikant R. (1994), ‘Fast Algorithms for Mining Association rules’, Proc. 20th VLDB conference, Santiago, Chile

      [3] Narra S. et al. (2014), ‘An efficient algorithm for mining coherent association rules’, International Journal of Computer Applications, Vol 6, No 2 https://doi.org/10.5120/16769-6336.

      [4] Brin S. et al. ‘Beyond Market Baskets: Generalizing Association Rules to Correlations’, in Proceedings of the ACM SIGMOD Conference, pp. 265-276 https://doi.org/10.1145/253260.253327.

      [5] Fayyad U, (1997),‘Data Mining and Knowledge Discovery in Databases: Implications from scientific databases’, In Proc. of the 9th Int. Conf. on Scientific and Statistical Database Management, Olympia, Washington, USA, pp. 2-11 https://doi.org/10.1109/SSDM.1997.621141.

      [6] Park J. et al. (1995) ,’Effective Hash-Based Algorithm for Mining Association’, Proceedings of ACM SIGMOD International Conference on Management of Data, San Jose, CA, pp. 175 – 186 https://doi.org/10.1145/568271.223813.

      [7] Kumbhar S. L. et al. (2015), ‘Pattern discovery using Apriori and Ch- Search Algorithm’, International Journal of Computational Engineering Research, Vol 5, No 3

      [8] K.Raja & Shiva Prasad T., ’Association Rule Mining using Apriori algorithm for food dataset’, available at https://www.academia.edu/ 8387094/ Association_Rule_ Mining_ using_ Apriori_algorithm_For_food_dataset

      [9] Manisha Kundal & Dr Parminder Kaur (2015), ’Various Frequent itemset based on Data Mining Technique’, International Research Journal of Engineering and Technology, Vol 02, No 3

      [10] Chen C. et al. (2014), ‘A Projection-based Approach for mining highly coherent Association rules’, Springer Publishing Switzerland https://doi.org/10.1007/978-3-319-07776-5_8.

      [11] Pei M. et al. , ‘Feature Extraction using genetic algorithm’, Case-Center for Computer-aided Engineering and Manufacturing W., Department of Computer Science

      [12] Ghosh S. et al. (2010), ‘Mining frequent item sets using Genetic Algorithm’, International Journal of Artificial Intelligence and Applications, Vol 1, No 4

      [13] Sharma S. et al. (2011), ‘Efficiency of Spiral Model by applying Genetic Algorithm’, International Journal of Computer Science and Technology, Vol 2, No 2

      [14] Sharma A. et al. (2012), ‘A Survey of Association Rule Mining Using Genetic Algorithm’, International Journal of Computer Applications and Information Technology, Vol 1, No 2

      [15] Dandu S. et al. (2013),’ Improved Algorithm for Frequent Item sets Mining Based on Apriori and FP-Tree’, Global Journal of Computer Science and Technology Software & Data Engineering, Vol 13, No 2

      [16] Kavya T & Sasi kumar R (2015), ‘Finding of repeated itemsets using Genetic Algorithm’, International Journal of Engineering Sciences & Research, Vol 4, No 7

      [17] Patel U.K. (2016) ‘Optimization of Association Rule Mining using Genetic Algorithm’, Conference Proceeding of International Conference on Recent Innovation in Science, Technology and Management.

      [18] Akilandeswari S. et al (2015),’A novel approach to mine infrequent weighted itemset using coherent rule mining algorithm, Indian Journal of Innovations and Developments, Vol 4, No 3

  • Downloads

  • How to Cite

    Sharma, S., & Bhatia, S. (2017). A study of frequent itemset mining techniques. International Journal of Engineering & Technology, 6(4), 141-144. https://doi.org/10.14419/ijet.v6i4.8300

    Received date: 2017-08-30

    Accepted date: 2017-09-11

    Published date: 2017-10-14