Proceedings ArticleDOI
Web usage mining tool by integrating sequential pattern mining with graph theory
Vinayak Musale,Devendra Chaudhari +1 more
- pp 160-163
TLDR
The improved approach is discussed which integrates sequential pattern mining with graph theory and design of web usage mining tool with improved approach with results are discussed.Abstract:
In this era, the web usage mining plays one of the important role in analyzing and improving performance of web applications. Initially in this paper, the concept of web usage mining has been introduced along with Improved AprioriAll algorithm which is the base algorithm for the proposed tool along with its limitation. The improved approach is discussed which integrates sequential pattern mining with graph theory. In the next part, design of web usage mining tool with improved approach is discussed. Implementation details of the tool are discussed along with the results. The last part covers how the raw result from the proposed tool can be further visualized and analyzed using new technologies like D3.js and Neo4j. The future scope of the proposed tool is mentioned at the end of the paper.read more
Citations
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References
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Journal ArticleDOI
Web usage mining: discovery and applications of usage patterns from Web data
TL;DR: Web usage mining is the application of data mining techniques to discover usage patterns from Web data, in order to understand and better serve the needs of Web-based applications as mentioned in this paper, where preprocessing, pattern discovery, and pattern analysis are described in detail.
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TL;DR: This paper establishes terminology to frame the problem of reliably determining usage of WWW resources while reviewing current practice and their shortcomings and argues that server-side sampling provides more reliable and useful usage data while requiring no change to the current HTTP protocol and enhancing user privacy.
Proceedings ArticleDOI
Page quality: in search of an unbiased web ranking
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