Implementation of Data Mining Technique for Determining K-Most Demanding Products

Authors

  • Advait Pundlik  BE Students, Department of Computer science and Engineering, Priyadarshini Bhagwati College of Engineering, Nagpur, Maharashtra, India
  • Vaibhav Hood  BE Students, Department of Computer science and Engineering, Priyadarshini Bhagwati College of Engineering, Nagpur, Maharashtra, India
  • Pawan Satpute  BE Students, Department of Computer science and Engineering, Priyadarshini Bhagwati College of Engineering, Nagpur, Maharashtra, India
  • Utkarsh Mandade  BE Students, Department of Computer science and Engineering, Priyadarshini Bhagwati College of Engineering, Nagpur, Maharashtra, India
  • Ankita Tripathi  BE Students, Department of Computer science and Engineering, Priyadarshini Bhagwati College of Engineering, Nagpur, Maharashtra, India
  • Prof. Kapil Hande  Assistant Professor, Department of Computer science and Engineering, Priyadarshini Bhagwati College of Engineering, Nagpur, Maharashtra, India

Keywords:

Algorithm for Knowledge Management, Data Mining, Decision Support, Performance Evaluation of Algorithm

Abstract

This paper formulates an issue for production design as k-most demanding products (k-MDP). Given an arrangement of clients demanding a specific kind of products with numerous traits, an arrangement of existing products of the sort, an arrangement of applicant products that organization can offer, and a positive whole number k, it causes the organization to choose k products from the hopeful products to such an extent that the normal number of the aggregate clients for the k products is augmented. One avaricious algorithm is utilized to discover surmised answer for the issue. Endeavour is likewise made to locate the ideal arrangement of the issue by evaluating the normal number for the aggregate clients of an arrangement of k competitor products for diminishing the pursuit space of the ideal arrangement.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

Issue

Volume 3, Issue 4, March-April-2018

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Advait Pundlik, Vaibhav Hood, Pawan Satpute, Utkarsh Mandade, Ankita Tripathi, Prof. Kapil Hande, " Implementation of Data Mining Technique for Determining K-Most Demanding Products, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 4, pp.76-81, March-April-2018.