@article{MAKHILLAJIT201615206428,
    title = {Optimizing Web Log Data to Perceive User Behavior},
    journal = {Asian Journal of Information Technology},
    volume = {15},
    number = {20},
    pages = {3899-3904},
    year = {2016},
    issn = {1682-3915},
    doi = {ajit.2016.3899.3904},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2016.3899.3904},
    author = {B. Prasanna Kumar and},
    keywords = {Fuzzy C-means clustering,web log data,SVM,web usage mining,web usage analysis},
    abstract = {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.}
    }