TY  - JOUR
TI  - Implementation of Data Mining Technique for Determining K-Most Demanding Products
AU  - Advait Pundlik
AU  -  Vaibhav Hood
AU  -  Pawan Satpute
AU  -  Utkarsh Mandade
AU  -  Ankita Tripathi
AU  -  Prof. Kapil Hande
JO  - International Journal of Scientific Research in Computer Science, Engineering and Information Technology
PB  - Technoscience Academy
DA  - 2018/04/30
PY  - 2018
DO  - https://doi.org/10.32628/IJSRCSEIT
UR  - https://ijsrcseit.com/CSEIT1833128
VL  - 3
IS  - 4
SP  - 76	
EP  - 81
AB  - 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.