2022
DOI: 10.1108/jsit-12-2019-0264
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Modeling user preferences in online stores based on user mouse behavior on page elements

Abstract: Purpose Online businesses require a deep understanding of their customers’ interests to innovate and develop new products and services. Users, on the other hand, rarely express their interests explicitly. The purpose of this study is to predict users’ implicit interest in products of an online store based on their mouse behavior through various product page elements. Design/methodology/approach First, user mouse behavior data is collected throughout an online store website. Next, several mouse behavioral fea… Show more

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Cited by 6 publications
(3 citation statements)
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“…SD access control strategies in the open network environment mainly include: SD file operation action control: users at different levels have different permissions for different SD documents, including read, write, preview, execute, share, delete, edit, copy, print and other access permissions. Support the times limit of operation authority, such as the read-only times, forwarding times, copying times, printable copies, and copyable words of SD files; Time constraints on SD files, including start time, end time and cumulative times [10][11].…”
Section: Sd Access Control Strategymentioning
confidence: 99%
“…SD access control strategies in the open network environment mainly include: SD file operation action control: users at different levels have different permissions for different SD documents, including read, write, preview, execute, share, delete, edit, copy, print and other access permissions. Support the times limit of operation authority, such as the read-only times, forwarding times, copying times, printable copies, and copyable words of SD files; Time constraints on SD files, including start time, end time and cumulative times [10][11].…”
Section: Sd Access Control Strategymentioning
confidence: 99%
“…In [29] a study based on eye tracking and mouse tracking was developed on commercial and educational portals in Nigeria, using OGAMA software, in order to identify search and browsing patterns employed by users interacting with these web portals. In [30] a study was conducted using machine learning techniques and sequential computing with the main objective of predicting users' implicit interest in products of an online store based on their mouse behavior through various product page elements, which allows businesses to acquire the understanding of their customers interests to innovate and develop new products and services. In [23] a framework that employs methods for eye and mouse tracking, keyboard input, self-assessment questionnaire and artificial intelligence algorithms was proposed to evaluate user experience and categorize users in terms of performance profiles.…”
Section: Introductionmentioning
confidence: 99%
“…interconnectedness, time and attribute interaction information in social networks) to enable large-scale personalised inference. Their proposed model complements simultaneous advances in neural architecture selection and is able to accommodate the rapid addition of new applications in online platforms [7].Malvika Singh proposes a multi-level user behaviour visualisation framework that provides efficient visualisation of user behaviour data collected from production vehicles via telematics. Their approach visualises user behaviour data at three different levels: a Task Level View aggregates event sequence data generated through touchscreen interactions to visualise user flows; a Flow Level View allows comparison of individual flows based on selected metrics; and a Sequence Level View provides detailed insights into touch interactions, line of sight and driving behaviour.…”
Section: Introductionmentioning
confidence: 99%