Please use this identifier to cite or link to this item: https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4523
Title: Identify User behavior on digital devices by using digital footprints
Authors: NITHIANANTHAN, N.
Issue Date: 11-Aug-2021
Abstract: Now-a-days most of our time is spent using some form of digital technology such as search engines, news portals, social media websites or applications. Our presence on digital devices makes us engaged most of the time and leads us to become oblivious of our important work, resulting in a form of procrastination that decreases our productivity significantly. Some desktop and mobile applications have recently emerged to counter the problem by introducing various means of self-tracking to reduce the wasting of time and engage in productive activities. However, already available Soft wares/Systems suffer several limitations in terms of being static or providing a limited view of actions using one aspect only. To promote self-awareness that helps bring positive changes in individual’s performance, there is a need to present the data in a more convincing ways, bringing interaction to it and present the same data in different ways using both temporal and categorical dimensions. Framework is described to collects and processes the digital foot prints and creates a user behavior model to extract valuable and interesting temporal and categorical patterns regarding user behavior and interests. To discover the valuable behavior patterns from the individual’s data, different web usage mining techniques have been used. Finally, demonstrate interactive visualizations for the analysis and monitoring of behavior patterns with the goal of providing the individual with detailed understanding of his/her behavior.
URI: http://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4523
Appears in Collections:2020

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