基于网络访问日志的软行为生物识别技术预测消费者兴趣水平的研究

N. Nishiuchi, S. Aoki
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引用次数: 1

摘要

本文提出了一种软行为生物识别技术,利用网站上的访问日志来预测消费者对特定产品的兴趣水平。在实验中,受试者被要求在一些网站上完成购物任务。从查询中获取的某一类产品的兴趣水平与网站购买过程中的访问日志进行了对比分析。结果表明,不同兴趣水平的用户,其网络搜索行为模式和基于访问日志的某些参数存在明显差异。此外,在实验数据的基础上,利用支持向量机(SVM)测试了兴趣水平的自动分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on soft behavioural biometrics to predict consumer's interest level using web access log
This paper presents a soft behavioural biometrics to predict the consumer's interest level in a specific product using access log on websites. The experiments are conducted in a way where the subjects are asked to perform a shopping task on some websites. The comparative analysis is carried out between the interest level of one category product taken from the inquiry, and the access log during the purchasing process on websites. The results show that the behavioural patterns of the web searching and some parameters based on the access log are clearly different depending on the interest level. Moreover, based on the experiments' data, an automatic classification of the interest level is tested using support vector machine (SVM).
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