The increasing user mobility demands placed upon IT services necessitates an environment that enables users to access optimal services at any time and in any place. This study presents research conducted to develop a system that is capable of analyzing user IT service patterns and tendencies and provides the necessary service resources by sharing each user’s context information. First, each user’s context information is gathered to provide the multi-agent software training data necessary to describe user operations in a hybrid peer-to-peer (P2P) structured communication environment. Next, the data collected about each user’s mobile device is analyzed through a Bayesian based neural network system to identify the user’s tendency and extract essential service information. This information provides a communication configuration allowing the user access to the best communication service between the user’s mobile device and the local server at any time and in any place, thereby enhancing the ubiquitous computing environment.
Описание
A multi-agent based user context Bayesian neural network analysis system - Springer
%0 Journal Article
%1 noKey
%A Yoon, Hyogun
%A Lee, Malrey
%A Gatton, ThomasM.
%D 2010
%I Springer Netherlands
%J Artificial Intelligence Review
%K Bayesian agent context network neural
%N 3
%P 261-270
%R 10.1007/s10462-010-9174-x
%T A multi-agent based user context Bayesian neural network analysis system
%U http://dx.doi.org/10.1007/s10462-010-9174-x
%V 34
%X The increasing user mobility demands placed upon IT services necessitates an environment that enables users to access optimal services at any time and in any place. This study presents research conducted to develop a system that is capable of analyzing user IT service patterns and tendencies and provides the necessary service resources by sharing each user’s context information. First, each user’s context information is gathered to provide the multi-agent software training data necessary to describe user operations in a hybrid peer-to-peer (P2P) structured communication environment. Next, the data collected about each user’s mobile device is analyzed through a Bayesian based neural network system to identify the user’s tendency and extract essential service information. This information provides a communication configuration allowing the user access to the best communication service between the user’s mobile device and the local server at any time and in any place, thereby enhancing the ubiquitous computing environment.
@article{noKey,
abstract = {The increasing user mobility demands placed upon IT services necessitates an environment that enables users to access optimal services at any time and in any place. This study presents research conducted to develop a system that is capable of analyzing user IT service patterns and tendencies and provides the necessary service resources by sharing each user’s context information. First, each user’s context information is gathered to provide the multi-agent software training data necessary to describe user operations in a hybrid peer-to-peer (P2P) structured communication environment. Next, the data collected about each user’s mobile device is analyzed through a Bayesian based neural network system to identify the user’s tendency and extract essential service information. This information provides a communication configuration allowing the user access to the best communication service between the user’s mobile device and the local server at any time and in any place, thereby enhancing the ubiquitous computing environment.},
added-at = {2014-04-25T10:50:15.000+0200},
author = {Yoon, Hyogun and Lee, Malrey and Gatton, ThomasM.},
biburl = {https://www.bibsonomy.org/bibtex/21eb130153c921990c62c63d9f13efa42/timfan3939},
description = {A multi-agent based user context Bayesian neural network analysis system - Springer},
doi = {10.1007/s10462-010-9174-x},
interhash = {ca787fecd7a5115eeff39339a4a1ccce},
intrahash = {1eb130153c921990c62c63d9f13efa42},
issn = {0269-2821},
journal = {Artificial Intelligence Review},
keywords = {Bayesian agent context network neural},
language = {English},
number = 3,
pages = {261-270},
publisher = {Springer Netherlands},
timestamp = {2014-04-25T10:50:15.000+0200},
title = {A multi-agent based user context Bayesian neural network analysis system},
url = {http://dx.doi.org/10.1007/s10462-010-9174-x},
volume = 34,
year = 2010
}