Main Reference PaperEnhanced Model of Web Page Prediction using Page Rank and Markov Model, International Journal of Computer Applications, April 2016 [Java/J2EE].
  • To predict the web page, this work implements the web page prediction technique which combines clustering with markov rule and page ranking algorithm. In proposed work, the similar web pages are clustered using K-means clustering algorithm. The probability of each web page is calculated which determines the PageRank of web-pages. Then apply the Markov rule on each cluster to evaluate occurrences of each web pages visited and predict the web pages.

+ Description
  • To predict the web page, this work implements the web page prediction technique which combines clustering with markov rule and page ranking algorithm. In proposed work, the similar web pages are clustered using K-means clustering algorithm. The probability of each web page is calculated which determines the PageRank of web-pages. Then apply the Markov rule on each cluster to evaluate occurrences of each web pages visited and predict the web pages.

  • To predict the next web page from the current web page.

  • Reducing time consumption.

+ Aim & Objectives
  • To predict the next web page from the current web page.

  • Reducing time consumption.

  • A technique is contributed to improve the proposed scheme.

+ Contribution
  • A technique is contributed to improve the proposed scheme.

  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1 and J2EE

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1 and J2EE

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

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