Diego Fernández

Learn More
The technique of collaborative filtering is especially successful in generating personalized recommendations. More than a decade of research has resulted in numerous algorithms, although no comparison of the different strategies has been made. In fact, a universally accepted way of evaluating a collaborative filtering algorithm does not exist yet. In this(More)
The recommendation of queries, known as query suggestion, is a common practice on major Web Search Engines. It aims to help users to find the information they are looking for, and is usually based on the knowledge learned from past interactions with the search engine. In this paper we propose a new model for query suggestion, the Search Shortcut Problem,(More)
Collaborative filtering is a popular recommendation technique. Although researchers have focused on the accuracy of the recommendations, real applications also need efficient algorithms. An index structure can be used to store the rating matrix and compute recommendations very fast. In this paper we study how compression techniques can reduce the size of(More)
The performance evaluation of an IR system is a key point in the development of any search engine, and specially in the Web. In order to get the performance we are used to, Web search engines are based on large-scale distributed systems and to optimise its performance is an important aspect in the literature. The main methods, that can be found in the(More)
In the last years, recommender systems have achieved a great popularity. Many different techniques have been developed and applied to this field. However, in many cases the algorithms do not obtain the expected results. In particular, when the applied model does not fit the real data the results are especially bad. This happens because many times models are(More)
The importance of information systems is increasing every day. In order to ensure their right operation, it is necessary to analyze a huge amount of traffic generated by different devices. However, classical techniques for operation and management are reactive and not proactive, what can evolve in a failure in the system. In this work we propose a new(More)
Collaborative filtering is one of the most popular recommendation techniques. While the quality of the recommendations has been significantly improved in the last years, most approaches present poor efficiency and scalability. In this paper, we study several factors that affect the performance of a k-Nearest Neighbors algorithm, and we propose a distributed(More)
  • 1