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Adaptive Query Recommendation Techniques for Log Files Mining to Analysis User’s Session Pattern

by Durga Choudhary, Subhash Chandra Jat, Pankaj Kumar Sharma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 133 - Number 17
Year of Publication: 2016
Authors: Durga Choudhary, Subhash Chandra Jat, Pankaj Kumar Sharma
10.5120/ijca2016908085

Durga Choudhary, Subhash Chandra Jat, Pankaj Kumar Sharma . Adaptive Query Recommendation Techniques for Log Files Mining to Analysis User’s Session Pattern. International Journal of Computer Applications. 133, 17 ( January 2016), 22-27. DOI=10.5120/ijca2016908085

@article{ 10.5120/ijca2016908085,
author = { Durga Choudhary, Subhash Chandra Jat, Pankaj Kumar Sharma },
title = { Adaptive Query Recommendation Techniques for Log Files Mining to Analysis User’s Session Pattern },
journal = { International Journal of Computer Applications },
issue_date = { January 2016 },
volume = { 133 },
number = { 17 },
month = { January },
year = { 2016 },
issn = { 0975-8887 },
pages = { 22-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume133/number17/24006-2016908085/ },
doi = { 10.5120/ijca2016908085 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:31:30.659295+05:30
%A Durga Choudhary
%A Subhash Chandra Jat
%A Pankaj Kumar Sharma
%T Adaptive Query Recommendation Techniques for Log Files Mining to Analysis User’s Session Pattern
%J International Journal of Computer Applications
%@ 0975-8887
%V 133
%N 17
%P 22-27
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

System log files are very important part of any web application. System log files serves as the purpose of directory in various aspect of knowledge mining. There is a wide variety of logs to stock knowledge about the search patterns of the users. There might be lots of formats of availability of logs, each of web application can develop format of its own logs. Generally, IP, date and time of the request, result for the request (with code), transaction size, protocol, request description, browser and operating system used by the user are some of the important attributes of every request that get into the record of the log file. This paper presents the user’s behavioral search pattern by the query log files.

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Index Terms

Computer Science
Information Sciences

Keywords

Log Files Web Mining Query Recommendation Techniques.

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