Link prediction and path analysis using Markov chains
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Using the moving average rule in a dynamic web recommendation system: Research Articles
International Journal of Intelligent Systems
Personalized recommendation with adaptive mixture of markov models
Journal of the American Society for Information Science and Technology
Website browsing aid: A navigation graph-based recommendation system
Decision Support Systems
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Adaptive Web navigation is a dynamic field with an expansive range of diverse ramifications and a promise to solve and improve several link recommendation techniques. This paper surveys several of these recommendation techniques and implements an improvement on Moving Average Rule method. Moving Average rule incorporates an offline and an online phase where data preprocessing and development of Recommendation Engine is done. To avoid bottlenecks and improve the efficiency, our implementation technique incorporates these two phases and applies a distributed procedure to it. We apply the divide and conquer rule by compartmentalizing the task and employing three different web services to perform the task. The simulation model has been configured to cater to different users; a repository containing each user's current browsing history, and a profile of the prioritized recommendations, are also provided as separate links.