The lack of representative textual content in many resources suggests the study of additional metadata to improve classification tasks. Social bookmarking and cataloging sites provide an accessible way to increase available metadata in large amounts with user-provided annotations. In this chapter, the authors study and analyze the usefulness of social annotations for resource classification. Th...

This papers shows the results obtained by a non supervised method in the task of sentiment polarity detection on micro-blogs. This method does not need of training, but it also is self-constructed from millions of publications on the web. The results show the effectiveness of the proposal, openining a new way of facing sentiment analysis in micro-blogs.

In this paper we present a resource-centric application classification approach that monitors data flow along the path from main memory to the cores to locate spots of high resource utilization and potential resource contention. We designate three application classes, i.e. streaming applications, last-level cache sensitive applications and applications that restrict their activity either within...

We describe our participation in the TopicBased Chinese Message Polarity Classification Task, based on the restricted and unrestricted resources respectively. In the restricted resource based classification, we focus on the selection of parameters in a multi-class classification model with highly-biased training data. In the unrestricted resource based classification, we explore the distributed...