Predicting document access in large multimedia repositories
ACM Transactions on Computer-Human Interaction (TOCHI)
Life, death, and lawfulness on the electronic frontier
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
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
Deriving and verifying statistical distribution of a hyperlink-based Web page quality metric
Data & Knowledge Engineering
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The significance of modeling and measuring various attributes of the Web in part or as a whole is undeniable. In this paper, we consider the application of patterns in browsing behavior of users for predicting access to Web documents. We proposed two models for addressing our specification of the access prediction problem. The first lays out a preliminary statistical approach using observed distributions of interaccess times of individual documents in the collection. To overcome its deficiencies, we adapted a stochastic model for library circulations, i.e., Burrell's model, that accounts for differences in mean access rates ofWeb documents. We verified the assumptions of this model with experiments performed on a server log of accesses recorded over a six month period. Our results show that the model is reasonably accurate in predicting Web page access probabilities based on the history of accesses.