Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/2802
Title: Acquisition of User’s Learning Styles Using Log Mining Analysis through Web Usage Mining Process
Authors: Kolekar, S.V.
Sanjeevi, S.G
Bormane, D.S.
Keywords: E-learning
Log Mining Analysis
Adaptive Learning styles
Web Usage Mining
Issue Date: Jan-2011
Publisher: Smart Innovation, Systems and Technologies
Citation: 10.1007/978-3-642-22194-1_80
Abstract: Web Usage Mining is a broad area of Web Mining which is associated with the Patterns extraction from logging information produced by web server. Web log mining is substantially the important part of Web Usage Mining (WUM) algorithm which involves transformation and interpretation of the logging information to predict the patterns as per different learning styles. Ultimately these patterns are useful to classify various defined profiles. To provide personalized learning environment to the user with respect to Adaptive User Interface, Web Usage Mining is very essential and useful step to implement. In this paper we build the module of E-learning architecture based on Web Usage Mining to assess the User’s behavior through web log analysis.
Description: NITW
URI: http://localhost:8080/xmlui/handle/123456789/2802
Appears in Collections:Metallurgical and Materials Engineering

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