Please use this identifier to cite or link to this item:
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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 |
Files in This Item:
File | Description | Size | Format | |
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idt11-014.pdf | 252.27 kB | Adobe PDF | View/Open |
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