Web access prediction is an important research direction in Web mining. Markov models are well-suited for predicting Web access. Although higher-order Markov models have good predictions result, these models have several limitations associated with high state-space complexity and reduced coverage. These affect the prediction performance deeply. A new Web access prediction model, Hybrid-order Tree-like Markov Model (HTMM), is proposed in this article. The technique intelligently merges two methods: a tree-like Markov model method that aggregates the access sequences by pattern matching and a hybrid-order method that combines varying order Markov models so that the resulting model has a low state complexity, improved prediction accuracy, and retains high coverage. Experiments confirm its usefulness. It's suitable for applications in E-business, such as Web prefetching, link prediction, and recommendation.
%0 Journal Article
%1 dongshan2002markov
%A Dongshan, Xing
%A Junyi, Shen
%C Piscataway, NJ, USA
%D 2002
%I IEEE Educational Activities Department
%J Computing in Science and Engineering
%K chain diss inthesis markov model
%N 6
%P 34--39
%R 10.1109/MCISE.2002.1046594
%T A New Markov Model For Web Access Prediction
%U http://dx.doi.org/10.1109/MCISE.2002.1046594
%V 4
%X Web access prediction is an important research direction in Web mining. Markov models are well-suited for predicting Web access. Although higher-order Markov models have good predictions result, these models have several limitations associated with high state-space complexity and reduced coverage. These affect the prediction performance deeply. A new Web access prediction model, Hybrid-order Tree-like Markov Model (HTMM), is proposed in this article. The technique intelligently merges two methods: a tree-like Markov model method that aggregates the access sequences by pattern matching and a hybrid-order method that combines varying order Markov models so that the resulting model has a low state complexity, improved prediction accuracy, and retains high coverage. Experiments confirm its usefulness. It's suitable for applications in E-business, such as Web prefetching, link prediction, and recommendation.
@article{dongshan2002markov,
abstract = {Web access prediction is an important research direction in Web mining. Markov models are well-suited for predicting Web access. Although higher-order Markov models have good predictions result, these models have several limitations associated with high state-space complexity and reduced coverage. These affect the prediction performance deeply. A new Web access prediction model, Hybrid-order Tree-like Markov Model (HTMM), is proposed in this article. The technique intelligently merges two methods: a tree-like Markov model method that aggregates the access sequences by pattern matching and a hybrid-order method that combines varying order Markov models so that the resulting model has a low state complexity, improved prediction accuracy, and retains high coverage. Experiments confirm its usefulness. It's suitable for applications in E-business, such as Web prefetching, link prediction, and recommendation.},
acmid = {766276},
added-at = {2017-01-30T15:02:20.000+0100},
address = {Piscataway, NJ, USA},
author = {Dongshan, Xing and Junyi, Shen},
biburl = {https://www.bibsonomy.org/bibtex/2cab772c0f75546b4014b33264a5079b2/becker},
doi = {10.1109/MCISE.2002.1046594},
interhash = {b5757865376e7ce86fe9a3848a1a8fab},
intrahash = {cab772c0f75546b4014b33264a5079b2},
issn = {1521-9615},
issue_date = {November 2002},
journal = {Computing in Science and Engineering},
keywords = {chain diss inthesis markov model},
month = nov,
number = 6,
numpages = {6},
pages = {34--39},
publisher = {IEEE Educational Activities Department},
timestamp = {2017-12-20T16:57:09.000+0100},
title = {A New Markov Model For Web Access Prediction},
url = {http://dx.doi.org/10.1109/MCISE.2002.1046594},
volume = 4,
year = 2002
}