Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Identifying User Task Using Associative Classification


Affiliations
1 Department of Computer Science and Engineering, Rungta College of Engineering and Technology, Bhilai, Chhattisgarh, India
     

   Subscribe/Renew Journal


The explosive use of the web has lead to a massive increase of web sites and boosting the web mining technology. Analyzing and discovering the useful information from the data collected through web is the motive of web mining technology; which also incorporates identification of web user's task. If we have any procedure to find out user task on the basis of their behavior then we can increase the usability of the web. This paper is providing a new approach to identify the user task at the time of navigation through click stream. Using the web logs we have prepared data comprising different browsing events performed by the user. The prepared data has been applied to the new classification approach known as associative classifier; integrating classification and association rule mining. Our paper presents the performance of the CBA (Classification based on association) algorithm for identification of task performed by the web user. In this paper, we have also presented the number of rules generated with the variant support and confidence.

Keywords

Classification, Association Rule Mining, Associative Classifier, Decision Tree, CBA.
Subscription Login to verify subscription
User
Notifications
Font Size


Abstract Views: 273

PDF Views: 0




  • Identifying User Task Using Associative Classification

Abstract Views: 273  |  PDF Views: 0

Authors

Deepak Bhalla
Department of Computer Science and Engineering, Rungta College of Engineering and Technology, Bhilai, Chhattisgarh, India
Devesh Nerayan
Department of Computer Science and Engineering, Rungta College of Engineering and Technology, Bhilai, Chhattisgarh, India

Abstract


The explosive use of the web has lead to a massive increase of web sites and boosting the web mining technology. Analyzing and discovering the useful information from the data collected through web is the motive of web mining technology; which also incorporates identification of web user's task. If we have any procedure to find out user task on the basis of their behavior then we can increase the usability of the web. This paper is providing a new approach to identify the user task at the time of navigation through click stream. Using the web logs we have prepared data comprising different browsing events performed by the user. The prepared data has been applied to the new classification approach known as associative classifier; integrating classification and association rule mining. Our paper presents the performance of the CBA (Classification based on association) algorithm for identification of task performed by the web user. In this paper, we have also presented the number of rules generated with the variant support and confidence.

Keywords


Classification, Association Rule Mining, Associative Classifier, Decision Tree, CBA.