A Product Recommendation System using Vector Space Model and Association Rule

被引：4
|
作者：
Mukhopadhyay, Debajyoti [1 ,4 ]
Dutta, Ruma [2 ,4 ]
Kundu, Anirban [2 ,4 ]
Dattagupta, Rana [3 ]
机构：
[1] Calcutta Business Sch, DH Rd, Bishnupur 743503, India
[2] Netaji Subhash Engn Coll, Kolkata 700152, India
[3] Jadavpur Univ, Kolkata 700032, India
[4] WIDiCoReL, Kolkata 700095, India
来源：
ICIT 2008: PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY | 2008年
关键词：
e-commerce; vector space model; association rule; Cellular Automata (CA); Single Cycle Multiple Attractor Cellular Automata (SMACA);
D O I：
10.1109/ICIT.2008.48
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents an alternative product recommendation system for Business-to-customer e-commerce purposes. The system recommends the products to a new user. It depends on the purchase pattern of previous users whose purchase pattern are close to that of new user. The system is based on vector space model to find out the closest user profile among the profiles of all users in database. It also implements Association rule mining based recommendation system, taking into consideration the order of purchase, in recommending more than one product. To make the association rule memory-efficient, cellular automata is used.
引用
收藏
页码：279 / +
页数：2
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