How to cite this paper
Mittal, M., Pareek, S & Agarwal, R. (2015). Loss profit estimation using association rule mining with clustering.Management Science Letters , 5(2), 167-174.
Refrences
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Anand, S.S., Hughes, J.G., Bell, D.A., & Patrick, A.R. (1997). Tackling the cross-sales problem using data mining. Proceedings of the 2nd Pacific-Asia Conference on Knowledge Discovery & Data Mining (pp. 331-343). Hongkong.
Brijs, T., Swinnen, G., Vanhoof, K., & Wets, G. (2000). A data mining framework for optimal product selection in retail supermarket data: The generalized PROFSET model. Proceedings of the 6th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 300-304). New York, USA.
Brijs, T., Swinnen, G., Vanhoof, K., & Wets, G. (1999). Using association rules for product assortment decisions: A case study. Proceedings of the 5th ACM SIGKDD International Conference on Knowledge discovery & data mining (pp. 254-260). New York, USA.
Broder, A.Z., Glassman, S.C., Manasse, M.S., & Zweig, G. (1997). Syntactic clustering of the web. Journal of Computer Networks ISDN Systems, 29(8), 1157-1166.
Guha , S., Rastogi, R., & Shim, K. (2000). A robust clustering algorithm for categorical attributes. Information System, 25(5), 345-366.
Jaggi, C.K., Mittal, M., & Khanna, A. (2012). Effects of inspection on retailer & apos; s ordering policy for deteriorating items with time-dependent demand under inflationary conditions. International Journal of Systems & Science, 44(9), 1774-1782.
Jaggi, C.K., & Mittal, M. (2012). Retailer ordering policy for deteriorating items with initial inspection and allowable shortage under the condition of permissible delay in payments. International Journal of Applied Industrial Engineering, 1(1), 46-79.
Jaggi, C.K., & Mittal, M. (2011). Economic order quantity model for deteriorating items with imperfect quality. International Journal Revista Invetigacion Operacional, 32(2), 107-113.
Jaggi, C.K., Goel, S.K., & Mittal, M. (2013). Credit financing in economic ordering policies for defective items with allowable shortages. International Journal of Applied Mathematics & Computation, 219(10), 5268–5282.
Jaggi, C.K., Goel, S.K., & Mittal, M. (2011). Economic order quantity model for deteriorating items with imperfect quality and permissible delay on payments. International Journal of Industrial Engineering Computations, 2(2), 237-248.
Kaku, I. (2004). A data mining framework for classification of inventories. Proceedings of the 5th Asia pacific Industrial Engineering & Management Systems (pp. 450-455). Japan.
Kaku, I., & Xiao, Y. (2008). A new algorithm of inventory classification based on the association rules. International Journal of Services Sciences, 1(2), 148-163.
Lee, H.L., & Rosenblatt, M.J. (1987). Simultaneous determination of production cycles and inspection schedules in a production system. Management Science, 33(9), 1125-1137.
Maddah B., & Jaber M. Y. (2008). Economic production quantity model for items with imperfect quality: Revisited. International Journal of Production Economics, 112(2), 808-815.
Mittal, M., Pareek, S., & Agarwal, R., “Efficient ordering policy for imperfect quality items using association rule mining”. Encyclopedia of Information Science & Technology 3rd Ed. (pp. 773-786). United States, Information Science Publishing, 2014.
Papachristos, S., & Kontantaras, I. (2006). Economic ordering quantity models for items with imperfect quality. International Journal of Production Economics, 100(1), 148–154.
Porteus, E.L. (1986). Optimal lot sizing, process quality improvement and setup cost reduction. Operations Research, 34(1), 137-144.
Rosenblatt, M.J., & Lee, H.L. (1986). Economic production cycles with imperfect production processes. IIE Transactions, 18(1), 48-55.
Salameh, M.K., & Jaber, M.Y. (2000). Economic production quantity model for item with imperfect quality. International Journal of Production Economics, 64(1), 59-64.
Wang, K., Xu, C., & Liu, B. (1999). Clustering transactions using large items. ACM CIKM International Conference on Information & Knowledge Management (pp. 483-490). New York.
Wong, R.C., Fu, A.W., & Wang, K. (2005). Data mining for inventory item selection with cross-selling consideration. Data Mining & Knowledge Discovery, 11(1), 81–112.
Wong, R.C., Fu, A.W., & Wang K. (2003). MPIS: Maximal-profit item selection with cross-selling considerations. IEEE International Conference on Data Mining (pp. 371-378). Florida, USA.
Xiao, Y., Zhang, R., & Kaku, I. (2011). A new approach of inventory classification based on loss profit. Expert Systems with Applications, 38(8), 9382-9391.
Zhao, Q., & Bhowmick, S.S. (2003). Association rule mining: A survey, Center for Advanced Information Systems, Nanyang Technological University, Report No. 2003118, Singapore.
Anand, S.S., Hughes, J.G., Bell, D.A., & Patrick, A.R. (1997). Tackling the cross-sales problem using data mining. Proceedings of the 2nd Pacific-Asia Conference on Knowledge Discovery & Data Mining (pp. 331-343). Hongkong.
Brijs, T., Swinnen, G., Vanhoof, K., & Wets, G. (2000). A data mining framework for optimal product selection in retail supermarket data: The generalized PROFSET model. Proceedings of the 6th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 300-304). New York, USA.
Brijs, T., Swinnen, G., Vanhoof, K., & Wets, G. (1999). Using association rules for product assortment decisions: A case study. Proceedings of the 5th ACM SIGKDD International Conference on Knowledge discovery & data mining (pp. 254-260). New York, USA.
Broder, A.Z., Glassman, S.C., Manasse, M.S., & Zweig, G. (1997). Syntactic clustering of the web. Journal of Computer Networks ISDN Systems, 29(8), 1157-1166.
Guha , S., Rastogi, R., & Shim, K. (2000). A robust clustering algorithm for categorical attributes. Information System, 25(5), 345-366.
Jaggi, C.K., Mittal, M., & Khanna, A. (2012). Effects of inspection on retailer & apos; s ordering policy for deteriorating items with time-dependent demand under inflationary conditions. International Journal of Systems & Science, 44(9), 1774-1782.
Jaggi, C.K., & Mittal, M. (2012). Retailer ordering policy for deteriorating items with initial inspection and allowable shortage under the condition of permissible delay in payments. International Journal of Applied Industrial Engineering, 1(1), 46-79.
Jaggi, C.K., & Mittal, M. (2011). Economic order quantity model for deteriorating items with imperfect quality. International Journal Revista Invetigacion Operacional, 32(2), 107-113.
Jaggi, C.K., Goel, S.K., & Mittal, M. (2013). Credit financing in economic ordering policies for defective items with allowable shortages. International Journal of Applied Mathematics & Computation, 219(10), 5268–5282.
Jaggi, C.K., Goel, S.K., & Mittal, M. (2011). Economic order quantity model for deteriorating items with imperfect quality and permissible delay on payments. International Journal of Industrial Engineering Computations, 2(2), 237-248.
Kaku, I. (2004). A data mining framework for classification of inventories. Proceedings of the 5th Asia pacific Industrial Engineering & Management Systems (pp. 450-455). Japan.
Kaku, I., & Xiao, Y. (2008). A new algorithm of inventory classification based on the association rules. International Journal of Services Sciences, 1(2), 148-163.
Lee, H.L., & Rosenblatt, M.J. (1987). Simultaneous determination of production cycles and inspection schedules in a production system. Management Science, 33(9), 1125-1137.
Maddah B., & Jaber M. Y. (2008). Economic production quantity model for items with imperfect quality: Revisited. International Journal of Production Economics, 112(2), 808-815.
Mittal, M., Pareek, S., & Agarwal, R., “Efficient ordering policy for imperfect quality items using association rule mining”. Encyclopedia of Information Science & Technology 3rd Ed. (pp. 773-786). United States, Information Science Publishing, 2014.
Papachristos, S., & Kontantaras, I. (2006). Economic ordering quantity models for items with imperfect quality. International Journal of Production Economics, 100(1), 148–154.
Porteus, E.L. (1986). Optimal lot sizing, process quality improvement and setup cost reduction. Operations Research, 34(1), 137-144.
Rosenblatt, M.J., & Lee, H.L. (1986). Economic production cycles with imperfect production processes. IIE Transactions, 18(1), 48-55.
Salameh, M.K., & Jaber, M.Y. (2000). Economic production quantity model for item with imperfect quality. International Journal of Production Economics, 64(1), 59-64.
Wang, K., Xu, C., & Liu, B. (1999). Clustering transactions using large items. ACM CIKM International Conference on Information & Knowledge Management (pp. 483-490). New York.
Wong, R.C., Fu, A.W., & Wang, K. (2005). Data mining for inventory item selection with cross-selling consideration. Data Mining & Knowledge Discovery, 11(1), 81–112.
Wong, R.C., Fu, A.W., & Wang K. (2003). MPIS: Maximal-profit item selection with cross-selling considerations. IEEE International Conference on Data Mining (pp. 371-378). Florida, USA.
Xiao, Y., Zhang, R., & Kaku, I. (2011). A new approach of inventory classification based on loss profit. Expert Systems with Applications, 38(8), 9382-9391.
Zhao, Q., & Bhowmick, S.S. (2003). Association rule mining: A survey, Center for Advanced Information Systems, Nanyang Technological University, Report No. 2003118, Singapore.