We propose a novel method, based on concepts from expander graphs, to sample communities in networks. We show that our sampling method, unlike previous techniques, produces subgra...
A lot of work has been done on extracting the model of web user behavior. Most of them target server-side logs that cannot track user behavior outside of the server. Recently, a no...
Shingo Otsuka, Masashi Toyoda, Jun Hirai, Masaru K...
This paper studies an adaptive clustering problem. We focus on re-clustering an object set, previously clustered, when the feature set characterizing the objects increases. We prop...
Abstract. Fine-grained lock protocols with lock modes and lock granules adjusted to the various XML processing models, allow for highly concurrent transaction processing on XML tre...
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....