A study of retrospective and on-line event detection
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Machine Learning
Topic Extraction from News Archive Using TF*PDF Algorithm
WISE '02 Proceedings of the 3rd International Conference on Web Information Systems Engineering
A Wavelet-Based Model to Recognize High-Quality Topics on Web Forum
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
An automatic extraction method of word tendency judgement for specific subjects
International Journal of Computer Applications in Technology
Hot Topic Detection on BBS Using Aging Theory
WISM '09 Proceedings of the International Conference on Web Information Systems and Mining
Hi-index | 0.00 |
BBS, often referred to as forum, is a system that offers so much information, where people talk about various topics. Some topics are hot while others are unpopular. It’s rather a hard job for a person to find out hot topics in these tons of information. In this paper we introduce a system that automatically retrieves hot topics on BBS. Unlike some topic detection systems, this system not only discovers topics but also judges their hotness. Messages are first clustered into topics based on their lexical similarity. Then a BPNN (Back-Propagation Neural Network) based classification algorithm is used to judge the hotness of topic according to its popularity, its quality as well as its message distribution over time. We have conducted experiments over Yahoo! Message Board (Yahoo BBS) and retrieved satisfactory results.