Efficient Approach for Weblog Analysis Based on Maximum Frequency
Dharmendra Dangi1, Amit Bhagat2, Brijesh Bakariya3

1Dharmendra Dangi, Department of Computer Applications, Maulana Azad National Institute of Technology, Bhopal (M.P), India.
2Amit Bhagat, Department of Computer Applications, Maulana Azad National Institute of Technology, Bhopal (M.P), India.
3Brijesh Bakariya, Department of Computer Science and Engineering, I.K. Gujral Punjab Technical University, Hoshiarpur (Punjab), India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 14-17 | Volume-8 Issue-5, March 2019 | Retrieval Number: D2722028419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Internet provides various services where a person interacts with each other. When a person performs any activity by internet then all the records stored on a web server. The data stored on the server called weblog data. This weblog contain lots of information about users. Now every person can get any information on a click. The huge amount of information stored on server. If we want to get the desired information from web server then it has to use some data mining techniques. Frequent pattern mining is one of the techniques for getting patterns from weblog. In this paper proposed an algorithm and framework for Pattern Analysis based on Maximum Frequency of Weblog (PAMFW) and also proposed a framework for pattern analysis.
Keyword: Data Mining, Internet, Pattern Analysis, Web Server, Weblog.
Scope of the Article: Predictive Analysis