—Traditional clustering techniques are inapplicable to problems where the relationships between data points evolve over time. Not only is it important for the clustering algorith...
Lijun Wang, Manjeet Rege, Ming Dong, Yongsheng Din...
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
Abstract—This paper introduces a knowledge-driven approach to real-time, continuous activity recognition based on multisensor data streams in smart homes. The approach goes beyon...
—Online learning algorithms often have to operate in the presence of concept drifts. A recent study revealed that different diversity levels in an ensemble of learning machines a...
—Preparing a data set for analysis is generally the most time consuming task in a data mining project, requiring many complex SQL queries, joining tables and aggregating columns....
—If past versions of XML documents are retained, what of the various integrity constraints defined in XML Schema on those documents? This paper describes how to interpret such c...
Faiz Currim, Sabah Currim, Curtis E. Dyreson, Rich...
—Computing interesting measures for data cubes and subsequent mining of interesting cube groups over massive datasets are critical for many important analyses done in the real wo...
Arnab Nandi, Cong Yu, Philip Bohannon, Raghu Ramak...
— This paper presents a method for identifying a set of dense subgraphs of a given sparse graph. Within the main applications of this “dense subgraph problem”, the dense subg...
—Search engine companies collect the “database of intentions”, the histories of their users’ search queries. These search logs are a gold mine for researchers. Search engin...
— Recommender systems are becoming increasingly important to individual users and businesses for providing personalized recommendations. However, while the majority of algorithms...