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A Survey on User Navigation Pattern Prediction from Web Log Data

Yogesh Bhalerao1 , P. P. Rokade2

Section:Survey Paper, Product Type: Journal Paper
Volume-3 , Issue-5 , Page no. 133-137, May-2015

Online published on May 30, 2015

Copyright © Yogesh Bhalerao , P. P. Rokade . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Yogesh Bhalerao , P. P. Rokade, “A Survey on User Navigation Pattern Prediction from Web Log Data,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.5, pp.133-137, 2015.

MLA Style Citation: Yogesh Bhalerao , P. P. Rokade "A Survey on User Navigation Pattern Prediction from Web Log Data." International Journal of Computer Sciences and Engineering 3.5 (2015): 133-137.

APA Style Citation: Yogesh Bhalerao , P. P. Rokade, (2015). A Survey on User Navigation Pattern Prediction from Web Log Data. International Journal of Computer Sciences and Engineering, 3(5), 133-137.

BibTex Style Citation:
@article{Bhalerao_2015,
author = {Yogesh Bhalerao , P. P. Rokade},
title = {A Survey on User Navigation Pattern Prediction from Web Log Data},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2015},
volume = {3},
Issue = {5},
month = {5},
year = {2015},
issn = {2347-2693},
pages = {133-137},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=493},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=493
TI - A Survey on User Navigation Pattern Prediction from Web Log Data
T2 - International Journal of Computer Sciences and Engineering
AU - Yogesh Bhalerao , P. P. Rokade
PY - 2015
DA - 2015/05/30
PB - IJCSE, Indore, INDIA
SP - 133-137
IS - 5
VL - 3
SN - 2347-2693
ER -

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Abstract

This paper proposes a survey of Web Page Prediction Methods. Prefetching of Web pages has been mostly used to reduce the access latency problem of the WWW users. However, if Prefetching of Web page is not accurate and Prefetched web pages are not visited by the users in their accesses, the limited bandwidth of network and services of Data Center and Cloud will not be used efficiently and may face the problem of access delay. Therefore, it is critical that we need an effective prediction method during prefetching of Services. The Markov models have been widely used to predict and analyze users navigational behavior. All the activities of web users have been saved in web log files. The stored users session is used to extract popular web navigation paths traverse and predict current users next web page Action in domain.

Key-Words / Index Term

Clustering,Classification,Recommender,N-Grams, User Sessions, Web Usage Mining

References

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