Study on soft behavioural biometrics to predict consumer's interest level using web access log
by Nobuyuki Nishiuchi; Seima Aoki
International Journal of Biometrics (IJBM), Vol. 11, No. 3, 2019

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).

Online publication date: Thu, 18-Jul-2019

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