Neuro-Fuzzy Based Hybrid Model for Web Usage Mining

被引:7
|
作者
Shivaprasad, G. [1 ]
Reddy, N. V. Subba [1 ]
Acharya, U. Dinesh [1 ]
Aithal, Prakash K. [1 ]
机构
[1] Manipal Univ, Manipal Inst Technol, Dept CSE, Manipal 576104, Karnataka, India
来源
ELEVENTH INTERNATIONAL CONFERENCE ON COMMUNICATION NETWORKS, ICCN 2015/INDIA ELEVENTH INTERNATIONAL CONFERENCE ON DATA MINING AND WAREHOUSING, ICDMW 2015/NDIA ELEVENTH INTERNATIONAL CONFERENCE ON IMAGE AND SIGNAL PROCESSING, ICISP 2015 | 2015年 / 54卷
关键词
Feed forward neural network; Fuzzy C means clustering; User identification; User session identification; Web log data;
D O I
10.1016/j.procs.2015.06.038
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Web Usage mining consists of three main steps: Pre-processing, Knowledge Discovery and Pattern Analysis. The information gained from the analysis can then be used by the website administrators for efficient administration and personalization of their websites and thus the specific needs of specific communities of users can be fulfilled and profit can be increased. Also, Web Usage Mining uncovers the hidden patterns underlying the Web Log Data. These patterns represent user browsing behaviours which can be employed in detecting deviations in user browsing behaviour in web based banking and other applications where data privacy and security is of utmost importance. Proposed work pre-process, discovers and analyses the Web Log Data of Dr. T.M.A.PAI polytechnic website. A neuro-fuzzy based hybrid model is employed for Knowledge Discovery from web logs. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:327 / 334
页数:8
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