Weight-vector based approach for product recommendation in e-commerce

被引：0

作者：

Prasad, B ^{[1
]}

机构：

[1] Georgia SW State Univ, Sch Comp & Informat Sci, Americus, GA 31709 USA

来源：

INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2002 | 2002年 / 2412卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a knowledge-based product retrieval and recommendation system for e-commerce. The system is based on the observation that, in Business to Customer (B2C) e-commerce, customers' preferences naturally cluster into groups. Customers belonging to the same cluster have very similar preferences for product selection. The system is primarily based on product classification hierarchy. The hierarchy contains weight vectors. The system learns from experience. The learning is in the form of weight refinement based on customer selections. The learning resembles radioactive decay in some situations. Labor profile domain has been taken up for system implementation. The results are at the preliminary stage, and the system is not yet evaluated completely.

引用

页码：200 / 205

页数：6

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