An approach to intelligent Web pre-fetching based on hidden Markov model
X. Jin, and H. Xu. Decision and Control, 2003. Proceedings. 42nd IEEE Conference on, 3, page 2954 - 2958 Vol.3. (December 2003)
DOI: 10.1109/CDC.2003.1273075
Abstract
With the exponential growth of information on the Web, Internet has become one of the most important information sources. However, due to limitation of the network bandwidth, users always have to bear with long time waiting. Web pre-fetching solution is one of the most popular strategies, which is proposed for reducing the perceived access delay and improving the service quality of Web server. This paper proposes a pre-fetching model based on the hidden Markov model (HMM), and utilizes HMM to capture and mine the latent information requirement concepts that the user's access path contains and to make semantic-based pre-fetching decisions. Experimental results show that our scheme has better predictive pre-fetching precision and evidently reduces the users' access time.
Description
IEEE Xplore - An approach to intelligent Web pre-fetching based on hidden Markov model
%0 Conference Paper
%1 jin2003approach
%A Jin, Xin
%A Xu, Huanqing
%B Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
%D 2003
%K CTII:WS1213 hidden hmm markov master model prefetching uni web ws1213
%P 2954 - 2958 Vol.3
%R 10.1109/CDC.2003.1273075
%T An approach to intelligent Web pre-fetching based on hidden Markov model
%U http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1273075&tag=1
%V 3
%X With the exponential growth of information on the Web, Internet has become one of the most important information sources. However, due to limitation of the network bandwidth, users always have to bear with long time waiting. Web pre-fetching solution is one of the most popular strategies, which is proposed for reducing the perceived access delay and improving the service quality of Web server. This paper proposes a pre-fetching model based on the hidden Markov model (HMM), and utilizes HMM to capture and mine the latent information requirement concepts that the user's access path contains and to make semantic-based pre-fetching decisions. Experimental results show that our scheme has better predictive pre-fetching precision and evidently reduces the users' access time.
@inproceedings{jin2003approach,
abstract = { With the exponential growth of information on the Web, Internet has become one of the most important information sources. However, due to limitation of the network bandwidth, users always have to bear with long time waiting. Web pre-fetching solution is one of the most popular strategies, which is proposed for reducing the perceived access delay and improving the service quality of Web server. This paper proposes a pre-fetching model based on the hidden Markov model (HMM), and utilizes HMM to capture and mine the latent information requirement concepts that the user's access path contains and to make semantic-based pre-fetching decisions. Experimental results show that our scheme has better predictive pre-fetching precision and evidently reduces the users' access time.},
added-at = {2012-11-20T13:55:55.000+0100},
author = {Jin, Xin and Xu, Huanqing},
biburl = {https://www.bibsonomy.org/bibtex/2379b6bd9cf2714b24fcd7287f9210fa8/telekoma},
booktitle = {Decision and Control, 2003. Proceedings. 42nd IEEE Conference on},
description = {IEEE Xplore - An approach to intelligent Web pre-fetching based on hidden Markov model},
doi = {10.1109/CDC.2003.1273075},
interhash = {4e96e426e7a24557206f45d954769611},
intrahash = {379b6bd9cf2714b24fcd7287f9210fa8},
issn = {0191-2216},
keywords = {CTII:WS1213 hidden hmm markov master model prefetching uni web ws1213},
month = {dec.},
pages = { 2954 - 2958 Vol.3},
timestamp = {2012-11-20T13:55:55.000+0100},
title = {An approach to intelligent Web pre-fetching based on hidden Markov model},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1273075&tag=1},
volume = 3,
year = 2003
}