Message retrieval and classification from chat room servers using Bayesian networks

Debbie Zhang; Simeon J. Simoff; John K. Debenham

Message retrieval and classification from chat room servers using Bayesian networks

Debbie Zhang, Simeon J. Simoff, John K. Debenham

Research output: Chapter in Book / Conference Paper › Conference Paper

Abstract

Chat rooms and newsgroup on the internet is a valuable, and often free of charge, source of information. In this paper, a design of smart chat room bots that automatically retrieve and filter on line messages is proposed. The design is based on internet technology and Bayesian Networks. Technical details of connecting to and retrieving data from web based chat room servers are presented. A Naive Bayesian network classifier is implemented using frequency of the keywords that mostly appear in the selecting messages as input features. A prototype of such a message classification system has been implemented. It has been trialed on detecting investment related messages from four Australian chat room sites.

Original language	English
Title of host publication	ICIIP 2006: Proceedings of the International Conference on Intelligent Information Processing, 20-23 September, 2006, Adelaide Australia
Publisher	Springer
Number of pages	6
Publication status	Published - 2006
Event	International Conference on Intelligent Information Processing - Duration: 1 Jan 2006 → …

Conference

Conference	International Conference on Intelligent Information Processing
Period	1/01/06 → …

Keywords

information storage and retrieval systems
Bayesian statistical decision theory
web mining
data mining
online chat groups
messages

Cite this

@inproceedings{75f12e1cf1624e439b352ee60a2531d8,

title = "Message retrieval and classification from chat room servers using Bayesian networks",

abstract = "Chat rooms and newsgroup on the internet is a valuable, and often free of charge, source of information. In this paper, a design of smart chat room bots that automatically retrieve and filter on line messages is proposed. The design is based on internet technology and Bayesian Networks. Technical details of connecting to and retrieving data from web based chat room servers are presented. A Naive Bayesian network classifier is implemented using frequency of the keywords that mostly appear in the selecting messages as input features. A prototype of such a message classification system has been implemented. It has been trialed on detecting investment related messages from four Australian chat room sites.",

keywords = "information storage and retrieval systems, Bayesian statistical decision theory, web mining, data mining, online chat groups, messages",

author = "Debbie Zhang and Simoff, {Simeon J.} and Debenham, {John K.}",

year = "2006",

language = "English",

booktitle = "ICIIP 2006: Proceedings of the International Conference on Intelligent Information Processing, 20-23 September, 2006, Adelaide Australia",

publisher = "Springer",

note = "International Conference on Intelligent Information Processing ; Conference date: 01-01-2006",

}

TY - GEN

T1 - Message retrieval and classification from chat room servers using Bayesian networks

AU - Zhang, Debbie

AU - Simoff, Simeon J.

AU - Debenham, John K.

PY - 2006

Y1 - 2006

N2 - Chat rooms and newsgroup on the internet is a valuable, and often free of charge, source of information. In this paper, a design of smart chat room bots that automatically retrieve and filter on line messages is proposed. The design is based on internet technology and Bayesian Networks. Technical details of connecting to and retrieving data from web based chat room servers are presented. A Naive Bayesian network classifier is implemented using frequency of the keywords that mostly appear in the selecting messages as input features. A prototype of such a message classification system has been implemented. It has been trialed on detecting investment related messages from four Australian chat room sites.

AB - Chat rooms and newsgroup on the internet is a valuable, and often free of charge, source of information. In this paper, a design of smart chat room bots that automatically retrieve and filter on line messages is proposed. The design is based on internet technology and Bayesian Networks. Technical details of connecting to and retrieving data from web based chat room servers are presented. A Naive Bayesian network classifier is implemented using frequency of the keywords that mostly appear in the selecting messages as input features. A prototype of such a message classification system has been implemented. It has been trialed on detecting investment related messages from four Australian chat room sites.

KW - information storage and retrieval systems

KW - Bayesian statistical decision theory

KW - web mining

KW - data mining

KW - online chat groups

KW - messages

UR - http://handle.uws.edu.au:8081/1959.7/489296

M3 - Conference Paper

BT - ICIIP 2006: Proceedings of the International Conference on Intelligent Information Processing, 20-23 September, 2006, Adelaide Australia

PB - Springer

T2 - International Conference on Intelligent Information Processing

Y2 - 1 January 2006

ER -

Message retrieval and classification from chat room servers using Bayesian networks

Abstract

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Keywords

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