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Reseach Article

Analysis of various Characteristics of Online User Behavior Models

by Dhanashree Deshpande, Shrinivas Deshpande
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 161 - Number 11
Year of Publication: 2017
Authors: Dhanashree Deshpande, Shrinivas Deshpande

Dhanashree Deshpande, Shrinivas Deshpande . Analysis of various Characteristics of Online User Behavior Models. International Journal of Computer Applications. 161, 11 ( Mar 2017), 5-10. DOI=10.5120/ijca2017913127

@article{ 10.5120/ijca2017913127,
author = { Dhanashree Deshpande, Shrinivas Deshpande },
title = { Analysis of various Characteristics of Online User Behavior Models },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2017 },
volume = { 161 },
number = { 11 },
month = { Mar },
year = { 2017 },
issn = { 0975-8887 },
pages = { 5-10 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2017913127 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-07T00:07:10.718135+05:30
%A Dhanashree Deshpande
%A Shrinivas Deshpande
%T Analysis of various Characteristics of Online User Behavior Models
%J International Journal of Computer Applications
%@ 0975-8887
%V 161
%N 11
%P 5-10
%D 2017
%I Foundation of Computer Science (FCS), NY, USA

Accurately identifying online user behavior is challenging task because while identifying malicious users, legitimate user should be separated correctly. Normal and suspicious users should be differentiated. Various classification methods are useful in this behavior detection process. Some of them give good performance and accurate results. Few metrics are used to deviate malicious users from good one. Security is the main concern need to provide to various online applications. Characteristics of user behavior can be studied on variety of OSNs, online news website, shopping web site for prize comparison, browsing behavior, search engine behavior through queries, users’ communication behavior through various online messaging platforms etc. This paper gives analysis of various characteristics of online user behavior models. User behavior methods are compared and analyzed.

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Index Terms

Computer Science
Information Sciences


k-means Markov Logic Network online user behavior social network user behavior model