Broad-coverage lexical resources such as WordNet are extremely useful. However, they often include many rare senses while missing domain-specific senses. We present a clustering a...
Background: A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free t...
This paper presents a cluster-based text categorization system which uses class distributional clustering of words. We propose a new clustering model which considers the global in...
Text clustering is one of the difficult and hot research fields in the text mining research. Combing Map Reduce framework and the neuron initialization method of VPSOM (vector pre...
Text representation is a central task for any approach to automatic learning from texts. It requires a format which allows to interrelate texts even if they do not share content w...