A Tibetan web Text Clustering model

In this paper we design and implement a Tibetan Topic Detection system to process the huge number of Tibetan language text on Web. It classifies the Tibetan text into several categories, performs clustering in each category to get the topic. According to the Tibetan grammar features, we give a Tibetan text clustering model TTCM (Tibetan Text Clustering Model) for the text from Internet news sites. We have studied the Feature representation, feature extraction, and clustering in the model separately. From the performed tests, It turns out that the text Clustering in this model has a good accuracy ratio and a good recall ratio. So it has high application value.