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Matrix factorization techniques such as the singular value decomposition (SVD) have had great success in recommender systems. We present a new perspective of SVD for constructing a latent space from the training data, which is justified by the theory of hy ...
In this thesis, we propose novel solutions to similarity learning problems on collaborative networks. Similarity learning is essential for modeling and predicting the evolution of collaborative networks. In addition, similarity learning is used to perform ...
Affine rank minimization algorithms typically rely on calculating the gradient of a data error followed by a singular value decomposition at every iteration. Because these two steps are expensive, heuristics are often used for approximations that reduce co ...
Face-to-face interactions are part of everyday life, ranging from family to working in teams and to global communities. Social psychologists have long studied these interactions with the aim of understanding behavior, motivations, and emergence of interact ...
Face-to-face interactions are part of everyday life, ranging from family to working in teams and to global communities. Social psychologists have long studied these interactions with the aim of understanding behavior, motivations, and emergence of interact ...
In conventional vector space model for information retrieval, query vector generation is imperfect for retrieval of precise documents which are de-sired by user. In this paper, we present a stochastic based approach for optimiz-ing query vector without use ...
We tackle the problem of improving the relevance of automatically selected tags in large-scale ontology-based information systems. Contrary to traditional settings where tags can be chosen arbitrarily, we focus on the problem of recommending tags (e.g., co ...
This study proposes a semi-automatic approach aimed at detecting conflict in conversations. The approach is based on statistical techniques capable of identifying turn-organization regularities associated with conflict. The only manual step of the process ...
This paper explores a crowdsourcing approach to the evaluation of a document recommender system intended for use in meetings. The system uses words from the conversation to perform just-in-time document retrieval. We compare several versions of the system, ...
This paper explores a crowdsourcing approach to the evaluation of a document recommender system intended for use in meetings. The system uses words from the conversation to perform just-in-time document retrieval. We compare several versions of the system, ...