Personalization recommendation based on customer's behavior under DMA-based sequential pattern

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Personalization recommendation based on customer's behavior under DMA-based sequential pattern

Received:2007-06-11 Revised:2007-08-19 Online:2007-11-01 Published:2007-11-01
Contact: Chen-Chen LIU

基于DMA的时间序列模式下顾客行为的个性化推荐

刘晨晨蒋国银

湖北经济学院

通讯作者: 刘晨晨

Abstract

Abstract: The E-commerce leads to the moreintensive competition among the entities, and personalization recommendation would be the breakthrough to increase the customer's loyalty and promote the profits. The dynamic mining algorithm was proposed and improved to realize the personalization recommendation based on customers purchase sequences. The definition of time contraint was put forward considering the impact of the length of the times compartmentalization and the selflearning function of the system was realized. The result of an imitating experiment indicates that the recommendation method proposed is feasible and effctive.

Key words: personalization recommendation, customer’s behavior, collaborative filtering

摘要： 动态挖掘算法考虑顾客随时间变化的动态行为轨迹的特性，采取动态追踪，以顾客的动态行为轨迹为依据实现对顾客的个性化推荐。由于行为轨迹中时间段划分跨度对推荐源数据实用价值存在影响，故提出了时间约束定义，同时完成了该算法中自动学习功能的实现。实验结果表明，基于该算法的推荐系统有较高的推荐准确度。

关键词: 个性化推荐, 顾客行为, 协同过滤

Chen-Chen LIU . Personalization recommendation based on customer's behavior under DMA-based sequential pattern[J]. Journal of Computer Applications.

刘晨晨蒋国银. 基于DMA的时间序列模式下顾客行为的个性化推荐[J]. 计算机应用.

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