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Prioritizing the Marketing Start Ups using Classification Algorithm


Affiliations
1 Assistant Professor, Department of Information Technology, M.Kumarasamy College of Engineering, Karur,Tamil Nadu, India
     

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Surveying the improvements and working of the available products in the global markets and establishing the new products is a hard job for in the current technology improving world, instead lot more market survey concerns are there to perform this task and provide the exact report. In existing system, a typical CF- based recommender system associates a user with a group of like-minded users based on their individual preferences over all the items, either explicit or implicit, and then recommends to the user some unobserved items enjoyed by the group. In the proposed system a new website is created to gather the information about the new products. After gathering the comments using classification algorithm ratings will be provided as per the products list.

Keywords

Recommender System, Classification algorithm.
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  • Prioritizing the Marketing Start Ups using Classification Algorithm

Abstract Views: 289  |  PDF Views: 0

Authors

Kanimozhi S
Assistant Professor, Department of Information Technology, M.Kumarasamy College of Engineering, Karur,Tamil Nadu, India

Abstract


Surveying the improvements and working of the available products in the global markets and establishing the new products is a hard job for in the current technology improving world, instead lot more market survey concerns are there to perform this task and provide the exact report. In existing system, a typical CF- based recommender system associates a user with a group of like-minded users based on their individual preferences over all the items, either explicit or implicit, and then recommends to the user some unobserved items enjoyed by the group. In the proposed system a new website is created to gather the information about the new products. After gathering the comments using classification algorithm ratings will be provided as per the products list.

Keywords


Recommender System, Classification algorithm.

References