1. Performance improvement of web server through log files cleaning
Authors : Akshay Gupta, M.a. Rizvi
Pages : 211-216
DOI : http://dx.doi.org/10.21172/1.73.530
Keywords : Usage mining, FP-Tree, K-Means, Data Cleaning, Data Preparation& Pre-processing, Pattern discovery. Abstract :Mining the web data is one of the most challenging tasks in the area of data mining and management for research scholars because there is huge heterogeneous, less structured data available on the web. Web server’s logs represent actual usage. Such data have been used for usage-based testing and quality assurance and also for understanding user behavior and guiding user interface design. By analyzing these logs, Web workload was characterized and used to suggest performance enhancements for Web servers. Data preparation techniques and algorithms can be used to process the raw Web server logs, and then mining can be performed to discover users’ visitation patterns for further usability analysis. In this research proposal it is proposed to extract actual user behavior from Web server logs, capture user behavior and also proposed a method which can filter out plenty of irrelevant log values based on the complex prefix of their uniform resource locator. This work will improve data quality of web logs by further filtering out more URL requests comparing with traditional data cleaning methods and analyze the results.
Citing this Journal Article :Akshay Gupta, M.a. Rizvi, "Performance improvement of web server through log files cleaning", Volume 7 Issue 3 - September 2016, 211-216
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