Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Reference :

    1. Nikky Rai, Susheel Jain and Anurag Jain, “Mining Positive and Negative Association Rule from Frequent and Infrequent Pattern Based on IMLMS_GA,” International Journal of Computer Applications, vol 77, September 2013.
    2. Ling Zhou, and Stephen Yau, “Efficient Association Rule Mining among Both Frequent and Infrequent Items,” An International Journal of Computers and Mathematics with Applications,” pp. 737-749, 2007.
    3. J. Jaya, and S.V.Hemalatha, “A Survey of Frequent and Infrequent Weighted Itemset Mining Approaches,” International Journal of Innovative Research in Computer and Communication Engineering, vol. 2, Issue 10, pp. 6086-6090, October 2014.
    4. A.Varsur Jalpa, A., P. Desai Sonali, and B. Hathi Karishma, “ Performance Analysis of Rare Itemset Mining Algorithms,” Journal of Emerging Technologies and Innovative Research, vol. 2, Issue 2, February 2015.
    5. KalyaniTukaramBhandwalkar, and MansiBhonsle, “Study of Infrequent Itemset Mining Techniques,” International Journal of Engineering Research and General Science,” vol. 2, Issue 6, pp. 676-679, October 2014.
    6. Sonia Jadhav and G. M. Bhandari, ”A Review on Efficient Mining Approach of Infrequent Weighted Itemset,” International Journal of Advance Research in Computer Science and Management Studies, vol 2, Issue 11, November 2014.
    7. K.Hemanthakumar, and J.Nagamuneiah, “Study on Mining Weighted Infrequent Itemsets Using FP Growth,” International Journal of Engineering and Computer Science, vol 4, Issue 6, pp.12719-12723, June 2015.
    8. Luca Cagliero and Paolo Garza, “Infrequent Weighted Itemset Mining Using Frequent Pattern Growth,” IEEE Trans. on Knowledge and Data Engineering, vol. 26, no. 4, pp. 903- 915, April 2014.

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