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Singular value decomposition (SVD) has been used widely in the literature to recover the missing entries of a matrix. The basic principle in such methods is to assume that the correlated data is distributed with a low-rank structure. The knowledge of the low-rank structure is then used to predict the missing entries. SVD is based on the assumption that the data (user ratings) are distributed on a...
An algorithm named SMHP is proposed, which aims at improving the efficiency of Topic Detection. In SMHP, a T-MI-TFIDF model is designed by introducing mutual information (MI) and enhancing the weight of terms in the title. Then VSM is constructed according to terms' weight, and the dimension is reduced by combining H-TOPN and PCA. Then topics are grouped based on SMHP. Experiment results show the...
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