Loading...
Please wait, while we are loading the content...
Similar Documents
Enhanced Web Personalization for Improved Browsing Experience
| Content Provider | Semantic Scholar |
|---|---|
| Author | Wagh, Rajnikant Bhagwan Patil, J. B. |
| Copyright Year | 2017 |
| Abstract | A Web Personalization system is the process of customizing the Website to the needs of individual user or a set of users. It makes use of various data mining techniques such as association rule mining, sequential pattern discovery, clustering, classification etc. for accurate prediction of user future movements. Recent techniques for web personalization lag in appropriate prediction of user interests. To provide effective suggestions, we have developed a novel web personalization technique. The proposed work is based on finding appropriate weights among the web pages of a website. We have used distance measure of visit relationship as well as occurrence frequency measure of web pages for this purpose. The approach uses enhanced graph based partitioning algorithm for clustering of web pages and classify the current user activities more accurately. A Threshold value is used to make a decision among web pages for recommendation purpose. Our experimental results get around 61% accuracy, 34 % coverage and 44.23 % F1 measure. It helps to improve browsing experience of user. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.ripublication.com/acst17/acstv10n6_40.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
