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Article . 2011
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https://dx.doi.org/10.48550/ar...
Article . 2011
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Analysis of Web Logs And Web User In Web Mining

Authors: Joshila Grace; Maheswari; Dhinaharan Nagamalai;

Analysis of Web Logs And Web User In Web Mining

Abstract

Log files contain information about User Name, IP Address, Time Stamp, Access Request, number of Bytes Transferred, Result Status, URL that Referred and User Agent. The log files are maintained by the web servers. By analysing these log files gives a neat idea about the user. This paper gives a detailed discussion about these log files, their formats, their creation, access procedures, their uses, various algorithms used and the additional parameters that can be used in the log files which in turn gives way to an effective mining. It also provides the idea of creating an extended log file and learning the user behaviour.

12 pages,6 figures,CCSIT 2011

Keywords

Web usage mining, Network Security, FOS: Computer and information sciences, Computer Science - Databases, Web Log file, Databases (cs.DB), Log data, Log Level directive, Web servers

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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