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Enhancement in Next Web Page Recommendation with the help of Multi- Attribute Weight Prophecy
Authors(5) :-Prof. Umesh A. Patil, Avinash Kunnure, Vaibhav Herwade, Vijaykumar Dawarpatil, Satyawan Magar
In Today internet world has increasing number of websites so it’s the big task to get accurate data from large numbers of website. The web data mining is one of the challenging task .While performing the web page prediction pre-processing of the data from a web site. The necessity for predicting the user’s needs in order to enhance the usability and user maintenance of a web site is more than marked now a day’s lacking proper guidance, a visitor often wanders aimlessly without visiting significant pages, loses attention, and leaves the site earlier than expected. When they access the network, a large amount of data is generated and is stored in Web log files which can be used efficiently as many times user frequently searched the same type of Web pages recorded in the log files. These sequence can be considered as a web access pattern, valuable to find the user behavior Through this custom-made information, it’s quite easy to forecast the next set of pages user might visit based on the previously searched patterns, thereby reducing the browsing time of a user.
Prof. Umesh A. Patil, Avinash Kunnure, Vaibhav Herwade, Vijaykumar Dawarpatil, Satyawan Magar
Web usages mining, recommendation, web log analysis, session based predication, K-NN algorithm
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Published in : Volume 3 | Issue 3 | March-April 2017
Date of Publication : 2017-04-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 304-309
Manuscript Number : IJSRST173395
Publisher : Technoscience Academy
PRINT ISSN : 2395-6011
ONLINE ISSN : 2395-602X
Cite This Article :
Prof. Umesh A. Patil, Avinash Kunnure, Vaibhav Herwade, Vijaykumar Dawarpatil, Satyawan Magar, "Enhancement in Next Web Page Recommendation with the help of Multi- Attribute Weight Prophecy", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 3, Issue 3, pp.304-309, March-April-2017
URL : http://ijsrst.com/IJSRST173395