In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Recommender Systems (RS) aim at predicting items or ratings of items that the user are interested in. Collaborative Filtering (CF) algorithms such as user- and item-based methods ...
Karen H. L. Tso-Sutter, Leandro Balby Marinho, Lar...
We describe the integration of a structuredtext retrieval system (TextMachine) into an object-oriented database system (OpenODB). We use the external function capability of the da...
Collaborative filtering (CF) shares information between users to provide each with recommendations. Previous work suggests using sketching techniques to handle massive data sets i...