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7.149  Articles
1 of 716 pages  |  10  records  |  more records»
Low-rank matrix factorizations such as Principal Component Analysis (PCA), Singular Value Decomposition (SVD) and Non-negative Matrix Factorization (NMF) are a large class of methods for pursuing the low-rank approximation of a given data matrix. The conv... see more

Recommender System (RS) is successfully applied in predicting user preferences. For instance, RS has been used in many areas such as in e-commerce (for online shopping), in entertainments (music/movie/video clip... recommendation), and in e... see more

We present a novel framework to consequently identify occasions from search log information and produce storyboards where the occasions are orchestrated sequentially. We picked picture look log as the asset for occasion mining, as search logs can straight... see more

Subject combinations at A-level in Ugandan Senior Secondary Schools have made or marred the future career of many prospective students, many students have ended up doing courses they had not planned to do because they made wrong choices at their A-level. ... see more

Revised versionThe task of dialog management is commonly decomposed into two sequential subtasks: dialog state tracking and dialog policy learning. In an end-to-end dialog system, the aim of dialog state tracking is to accurately estimate the tr... see more

C. MacDuffee apparently was the first to point out, in private communications, that a full-rank factorization of a matrix A leads to an explicit formula for its Moore-Penrose’s inverse A+. Here we apply this idea of MacDuffee and the Singular Value Decomp... see more

Collaborative filtering suffers from the problems of data sparsity and cold start, which dramatically degrade recommendation performance. To help resolve these issues, we propose TrustSVD, a trust-based matrix factorization technique. By analyzing the soc... see more

Revised versionThe task of dialog management is commonly decomposed into two sequential subtasks: dialog state tracking and dialog policy learning. In an end-to-end dialog system, the aim of dialog state tracking is to accurately estimate the tr... see more

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