Web sites thematic classification using hidden Markov models
Lyonel Serradura, Mohamed Slimane, Nicole Vincent · 2002
There is more and more information available on the Internet. We need tools to help us extract the right piece of information. We have developed a classification algorithm tackling this issue in French. It distinguishes web pages classifying their text content into themes. We use Hidden Markov Models (HMM) to build this method named STCoL (Supervised Thematic Corpus Learning). Once themes are modeled with HMMs, STCoL is able to classify documents from different sources. This method is not only efficient but is also robust.