Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
We consider a challenging clustering task: the clustering of muti-word terms without document co-occurrence information in order to form coherent groups of topics. For this task, ...
This paper describes the participation of DAEDALUS team at the WebPS-3 Task 1, regarding Web People Search. The focus of our research is to evaluate and compare the computational r...
In this paper, a new language model, the Multi-Class Composite N-gram, is proposed to avoid a data sparseness problem for spoken language in that it is difficult to collect traini...
In supervised kernel methods, it has been observed that the performance of the SVM classifier is poor in cases where the diagonal entries of the Gram matrix are large relative to ...