Hybrid Association Rules to Classify and Discovering Item sets based on User Knowledge

Authors(2) :-R.Vijaya, Dr. M. Babu Reddy

Increase large luminous data is posing research concept to predict and effective analysis of data in different types of business oriented applications. Intelligence of business maintenance is an aggressive concept to provide analysis customers, employees and suppliers for more effective decision making. It is basic representation to update and enhance their business in different formats like quality of service, and achieve profitability for business organizations. To provide analysis of data effectively, traditionally some of the data mining approaches like Classification, Clustering and Association were used to provide and increase the efficiency in real time business organizations. Based on in depth analysis of data relates to data delivery, reporting and predictive analysis, data mining techniques have failure to elaborate business in real works. So it aims to explore the advanced and statistical techniques apart from existing data mining or modeling approaches. In this paper, we propose and implement a novel HDM approach (which consist Association rules and Classification rules) for effective analysis of large data sets. Our approach is increases the services like quality of service, customer service, and report generations in business organizations. Furthermore, hybrid data mining approach is designed to assist to user throughout data analyzing task. By applying our new approach over large data to integrate domain expert knowledge in post processing to reduce set of rules in business intelligence service analysis. Our experimental results show effective maintenance of customer service to reduce quality of filtered rules by domain expert knowledge with interactive process in real world business organizations.

Authors and Affiliations

Research Scholar, Computer Science Department, Rayalaseema University, Kurnool, Andhra Pradesh, India
Dr. M. Babu Reddy
HOD, Department of Computer Science, Krishna University, Machilipatnam, Andhra Pradesh, India

Intelligence of Business, Data mining, Hybrid approach, Classification, Clustering, Customer services, Quality of service and crystal reports.

  1. Santos. A.D.. Duarte. J.F., Reis. A., da Rocha. B., Neto. R., Paiva. R., 2001. The use of finite element simulation for optimization of metal forming and tool design. J. Mater. Process. Technol. 119.152-157.
  2. Du Ko.B, D. Kim, S. Hyung, B.B. Hwang, The influence of die geometry on the radial extrusion processes. Journal of Materials Processing Technology, 113 (2001) 109-114
  3. Lee D. J., Kim D. J., Kim B. M., New processes to prevent a flow defect in the combined forward-backward cold extrusion of a piston-pin. J. Mater. Process. Technol. 139, 422-427, 2003.
  4. Liu. G., Zhang. L.B., Hu. X.L., Wang. Z.R., Wang. R.W., Huang. S.D., Tang. Q.B.. 2004. Applications of numerical simulation to the analysis of bulk-forming processes-case studies. J. Mater. Process. Technol. 150, 56-61.
  5. Ishikawa T., Yukawa N., Yoshida Y., Tozawa Y., Analytical approach to elimination of surface micro-defects in forging. CIRP Ann. Manuf. Technol. 54, 249-252, 2005
  6. Giuliano G., Process design of the cold extrusion of a billet using finite element method. Mater. Des. 28, 726-729, 2007.
  7. Zhang. G.L.. Zhang. S.H.. Li. B.. Zhang. H.Q.. 2007. Analysis on folding defects of inner grooved copper tubes during ball spin forming. J. Mater. Process. Technol. 184. 393-400.
  8. Fu M. W., Yong M. S., Tong K. K., Danno A., Design solution evaluation for metal forming product development. Int. J. Adv. Manuf. Technol. 38, 249-257, 2008.
  9. Investigation of defect in combined precision extrusion process with multiple ram / I. Aliiev, L. Aliieva, P. Abhari, K. Goncharuk // XVI International scientific conference New technologies and achievements in metallurgy, material engineering and production engineering. – Series : Monographs. – Czestochowa, Poland, 2015. – ?48. – P. 90–93.
  10. Payman Abhari Investigation of load on the tools in precision radial extrusion process with multiple ram /Payman Abhari // XVII International scientific conference «New technologies and achievements in metallurgy, material engineering and production engineering» : Series: Monografie. - Nr 56. – Cz?stochowa, Poland, 2016 – ?. 330–333.

Publication Details

Published in : Volume 3 | Issue 5 | July-August 2017
Date of Publication : 2017-08-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 715-721
Manuscript Number : IJSRSET1844440
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

R.Vijaya, Dr. M. Babu Reddy, " Hybrid Association Rules to Classify and Discovering Item sets based on User Knowledge, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 5, pp.715-721, July-August-2017.
Journal URL : http://ijsrset.com/IJSRSET1844440

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