Improving Web User Navigation Prediction Using Web Usage Mining |
Author(s): |
| Palak Pravinbhai Patel , Sankalchand Patel College of Engineering, Visnagar; Rakesh K. Patel, Sankalchand Patel College of Engineering, Visnagar |
Keywords: |
| Web Mining, Preprocessing, Longest Common Subsequence |
Abstract |
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Web usage mining is the process of automatic discovery of user navigation pattern from the web log files or how the user is accessing page on World Wide Web. The interaction of user with the web gets recorded in the web log file at server side. These log files can be analyzed by various pattern discovery techniques. The discovered patterns can be used for Web Recommendations. By analyzing the web log, the next to be accessed by user can be predicted, and can be pre-send to client to minimize the network latency. There are various techniques like Markov Model, Longest Common Subsequence, Association Rule, Clustering etc. These techniques are used to predict user next request. In this paper, we use longest common subsequence algorithm to predict user navigation. LCS algorithms improve the accuracy and classify current user activities. |
Other Details |
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Paper ID: IJSRDV3I30372 Published in: Volume : 3, Issue : 3 Publication Date: 01/06/2015 Page(s): 3463-3467 |
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