REAL-TIME BROWSING ASSISTANT ON WEB
Journal: IADIS INTERNATIONAL JOURNAL ON WWW/INTERNET (Vol.16, No. 2)Publication Date: 2018-12-21
Authors : Syed Tauhid Zuhori; James Miller;
Page : 1-18
Keywords : Real-time Browsing Assistance System; Discrete Time Markov Chain Inference Process; Markovian Decision Process; Reinforcement Learning;
Abstract
Understanding user requirements based on their interactions with a website is becoming increasingly important. Hence, in this paper, a novel real-time navigation-support system is discussed. This system builds a personalized browsing assistant based on the current user request submitted to a web server. The process involves developing a behavior model using a Discrete Time Markov Chain (DTMCs) inference process. This is then used to monitor user activities, and thereafter suggest “where to go next”. Finally, it updates the model in real time using a Markovian Decision Process (MDP). To evaluate the system, we provide a user study, case studies and conduct experiments on two datasets to verify the effectiveness of our proposed system.
Other Latest Articles
- DATA PHILANTHROPY IN SOUTH AFRICAN ORGANISATIONS: ATTITUDES, READINESS AND PERCEIVED CONCERNS
- TRUST AND PRIVACY IN MESSAGING
- MEDIA INNOVATION AND BUSINESS MODELS: THE CASE OF END-TO-END IMMERSIVE AUDIOVISUAL SERVICES
- BLENDED LEARNING IN RESEARCH ORIENTED EDUCATION: TANGLE, AN EDUCATIVE SUITE FOR QUANTUM INFORMATION
- Prácticas Inclusivas e Interculturales destinadas al Alumnado recién llegado de otros Países a Cataluña
Last modified: 2019-12-13 22:04:10