A Paper on Multisite Framework for Web page Recommendation Using Incremental Mining

Authors(2) :-Mr. Rahul B. Patil, Prof. K. B. Manwade

Large amounts of information present on web due to that web user finds difficulty when surfing the web. Useful and Effective suggestions provided by Recommendation systems which help web users. User's future interest evaluate by using the learning and prediction models which learn user's behavior. Web page recommendation improves web user satisfaction and website usage. Semantic enhanced "Multisite framework for Web page Recommendation using Incremental Mining" improves web page recommendation. In which web page recommendation will be done by using multiple website in same domain. Will be give effective recommendation results given by Different sites. To identify and collect more appropriate web usage data Dynamic web page recommendations tool is generated. Related terms identified which help to generate more appropriate data. Incremental mining update web usage knowledge and updates the knowledge base.

Authors and Affiliations

Mr. Rahul B. Patil
PG Student, Ashokrao Mane Group of Institution, Vathar, Kolhapur, Maharashtra, India
Prof. K. B. Manwade
Associate Professor, Ashokrao Mane Group of Institution, Vathar, Kolhapur, Maharashtra, India

Incremental Mining, IPNAR, Semantic Network Model, Ontology, Semantic Knowledge, FWAP

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Publication Details

Published in : Volume 2 | Issue 4 | July-August 2016
Date of Publication : 2016-08-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 266-270
Manuscript Number : IJSRST162464
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Mr. Rahul B. Patil, Prof. K. B. Manwade, " A Paper on Multisite Framework for Web page Recommendation Using Incremental Mining", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 2, Issue 4, pp.266-270, July-August-2016.
Journal URL : http://ijsrst.com/IJSRST162464

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