An Efficient Algorithm Research to Web User Access Prediction

DOI

10.2991/meici-16.2016.241How to use a DOI?

Keywords

Access prediction; Feedback mechanism; Web log mining; Markov prediction; Association rule

Abstract

In order to enhance accuracy of the algorithms on user access prediction. The prediction algorithm based on Markov chain and association rule(PAMA), and Markov prediction model with feedback(MPMF) were proposed. The PAMA integrates the advantage of Markov chain and association rule well. It corrects the Markov prediction result on forward and reverse perspective, and gets the last prediction page. The MPMF adjusts the prediction algorithm dynamically according to user feedback mechanism and history prediction information, and then gets the prediction page at last. Theoretical analysis proves these two prediction methods with linear time complexity. Experiments result shows that the accuracy of PAMA and MPMF is good, so the prediction efficiency is also meeting the requirement.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Shaorong Feng
PY  - 2016/09
DA  - 2016/09
TI  - An Efficient Algorithm Research to Web User Access Prediction
BT  - Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)
PB  - Atlantis Press
SP  - 1156
EP  - 1162
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-16.2016.241
DO  - 10.2991/meici-16.2016.241
ID  - Feng2016/09
ER  -