Abstract
As per the today’s scenario, the current technology of modern trend is required to improve the performance by minimum effort, to find more valuable items, and to extract precious information for industry people from large dataset efficiently that contains sales transactions (e.g., collections of items bought by customers or details of a website frequentation). We are proposing novel approach Business Strategy Prediction System for Market Basket Analysis. It is to find that all existing algorithms are working to find the minimal frequent item set first, but here with the help of those methods, we are finding the maximal item set. When this algorithm encountered on dense data which having the large numbers of long patterns emerge that will give the more accurate and effective result which specify all of the frequent item sets.
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References
Sun W, Pan M, Qiang Y (2011) Improved association rule mining method based on t statistical. Appl Res Comput 28(6):2073–2076
Yong-qing W, Ren-hua Y, Pei-yu L (2009) An improved apriori algorithm for association rules of mining. IEEE
Chen Z, Shibang C, Song Q, Zhu C (2011) An improved apriori algorithm based on pruning optimization and transaction reduction. IEEE
Chang R, Liu Z (2011) An improved apriori algorithm. In: 2011 international conference on electronics and optoelectronics (ICEOE)
Wang H, Liu X (2011) The research of improved association rules mining apriori algorithm. In: 2011 eighth international conference on fuzzy systems and knowledge discovery (FSKD)
Han J, Kamber M (2007) Conception and technology of data mining. China Machine Press, Beijing
JN Wong (trans) (2003) Tutorials of data mining. Tsinghua University Press, Beijing
Yuan Y, Yang C, Huang Y, Mining D (2007) And the optimization technology and its application. Science Press, Beijing
Kon YS, Rounteren N (2010) Rare association rule mining and knowledge discovery: technologies for frequent and critical event detection. H ERSHEY. Information Science Reference, PA
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Jain, S., Sharma, N.K., Gupta, S., Doohan, N. (2018). Business Strategy Prediction System for Market Basket Analysis. In: Kapur, P., Kumar, U., Verma, A. (eds) Quality, IT and Business Operations. Springer Proceedings in Business and Economics. Springer, Singapore. https://doi.org/10.1007/978-981-10-5577-5_8
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DOI: https://doi.org/10.1007/978-981-10-5577-5_8
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