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 |
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| 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 |
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| Period | 1/01/06 → … |
Keywords
- information storage and retrieval systems
- Bayesian statistical decision theory
- web mining
- data mining
- online chat groups
- messages