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Discovering Time Constraint Association Rules in Web Server Log Files

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dc.contributor.author Lwin, Ei Zar
dc.contributor.author Oo, Khwar Nyo
dc.date.accessioned 2019-07-19T14:21:41Z
dc.date.available 2019-07-19T14:21:41Z
dc.date.issued 2017-12-27
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1090
dc.description.abstract Web mining generates web access patterns, web structures, regularity and dynamics of web contents. Association rules are used to describe what items are frequently bought together. One could also use them in web usage mining to describe the pages that are often visited together. This paper presents time-constraint association rules by extensions of Apriori algorithm, where Support and confidence ratios are also computed. Current web usage mining algorithms based on association rule do not consider the time sequence of web usage data. Time-constraint association used in this paper not only maintains the sequential information, but also set the time frame of the web usage data. In time constraint association rule, time ratios express the conditional probability of X and Y occurring in the time window defined by t1 and t2, given the fact that X and Y are accessed together in the same session. This system generates association rules based on time constraints; i.e; in which, access pattern occur in the same time frame. Rules generated from this system can be applied to recommender system, where there is more relationship between pages with time constraint. en_US
dc.language.iso en en_US
dc.publisher Eighth Local Conference on Parallel and Soft Computing en_US
dc.title Discovering Time Constraint Association Rules in Web Server Log Files en_US
dc.type Article en_US

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