A New Neural Network to Extract Topics in Dynamical Text
Xiao Pu · 2006
Recently,the analysis of dynamically evolving textual data has become to an active research field in Data Mining.For example,extracting topics in the Internet chat lines.The existing neural network methods are based on linear time-series model,which could extract topics very well.But it cannot decide which topic is the hot topic and the topics disturb each other.Since the topics is independent each other and the topics are self- correlation,a new neural network is derived.It can solve the mentioned problems.Simulation results on Yahoo chat room illustrate that our neu- ral network indeed extract meaningful and hot topics.And the disturbance between topics is very small.