TY  - JOUR
T1  - Optimizing Web Log Data to Perceive User Behavior
AU - Reddy, B. Prasanna Kumar AU - Rao, Duvvada Rajeswara 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 20
SP  - 3899
EP  - 3904
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.3899.3904
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.3899.3904
KW  - Fuzzy C-means clustering
KW  -web log data
KW  -SVM
KW  -web usage mining
KW  -web usage analysis
AB  - Day to day the information in world wide web is increasing tremendously along with number of users. So it was difficult for the web application/website admin to maintain huge amount of data about the user and his needs. With the help of web usage mining techniques, the user’s behavior can be extracted from log data. It helps in analyzing errors of a website so that website administrator or designer can improve their system. Clustering has a key role in analyzing web log data. In this study we propose aclustering method to help mining log data for understanding user behavior.
ER  -