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...
This paper proposes extending semi-supervised learning by allowing an ongoing interaction between a user and the system. The extension is intended to not only to speed up search fo...
This contribution addresses the development of new web sites reusing already existing contents from external sources. Unlike common links to other resources, which retrieves the w...
Abstract. Collecting relevance judgments (qrels) is an especially challenging part of building an information retrieval test collection. This paper presents a novel method for crea...
We consider the problem of recommending the best set of k items when there is an inherent ordering between items, expressed as a set of prerequisites (e.g., the course ‘Real Ana...