Online communities are connecting hordes of individuals and generating rich social network data. The social capital that resides within these networks is largely unknown. We propo...
Abstract— Today’s embedded systems are typically distributed and more often confronted with timevarying demands. Existing methodologies that optimize the partitioning of comput...
Skyline queries ask for a set of interesting points from a potentially large set of data points. If we are traveling, for instance, a restaurant might be interesting if there is n...
This work proposes a novel practical and general-purpose lossless compression algorithm named Neural Markovian Predictive Compression (NMPC), based on a novel combination of Bayesi...
We study the problem of integrating scattered online opinions. For this purpose, we propose to exploit structured ontology to obtain well-formed relevant aspects to a topic and us...