Distributed Learning Predictors through Web Log Mining using Bayesian Networks
Main Article Content
Abstract
Distributed learning discusses the various strategies in which learners are separated but communicate between themselves through the
learning coaches. This makes the learners improve the learning skills and decrease learning times. A large part of hidden information resides in
a weblog server (i.e.), user IP address, location, time, Number of entries. Web log designer can analyse these information and rank the weblogs
based on this information. In this paper weblog analysis of data is done through distributed system by using the Bayesian networks. The
behaviour of a web site’s users may change so that the designer can trace out the user behaviour from web log to make predictions, according to
the frequent patterns accessed through the log files For the classification purpose Bayesian classifier is used which is based on the probability
theory.
Keywords- weblogs; distributed node; distributed learner; Bayesian classifier; mining.
Downloads
Article Details
COPYRIGHT
Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
- The journal allows the author(s) to retain publishing rights without restrictions.
- The journal allows the author(s) to hold the copyright without restrictions.