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Title:
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A NOVEL REAL-TIME BROWSING ASSISTANCE SYSTEM BASED ON WEB USER BEHAVIOURS |
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Author(s):
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Syed Tauhid Zuhori and James Miller |
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ISBN:
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978-989-8533-82-1 |
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Editors:
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Pedro Isaías and Hans Weghorn |
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Year:
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2018 |
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Edition:
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Single |
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Keywords:
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Real-Time Suggestion, Markovian Decision Process, Reward, Q-Learning |
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Type:
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Full Paper |
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First Page:
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175 |
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Last Page:
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182 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Understanding user requirements based on their interactions with a website is becoming more important. Hence in this paper a novel real-time navigation-support system is discussed. This system builds a personalized browsing assistance based on the current user request submitted to a web server. The process involves developing the 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. |
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