Title: Study on soft behavioural biometrics to predict consumer's interest level using web access log
Authors: Nobuyuki Nishiuchi; Seima Aoki
Addresses: Faculty of System Design, Tokyo Metropolitan University, Tokyo, Japan ' Faculty of System Design, Tokyo Metropolitan University, Tokyo, Japan
Abstract: 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).
Keywords: soft biometrics; behavioural biometrics; consumer's interest level; web access log; web analytics; purchasing process; electric commerce site; automatic classification; support vector machine; SVM.
International Journal of Biometrics, 2019 Vol.11 No.3, pp.243 - 256
Available online: 23 May 2019 *Full-text access for editors Access for subscribers Purchase this article Comment on this article