In this paper, we present an algorithm that can classify large-scale text data with high classification quality and fast training speed. Our method is based on a novel extension o...
Dong Zhuang, Benyu Zhang, Qiang Yang, Jun Yan, Zhe...
We present a framework for clustering distributed data in unsupervised and semi-supervised scenarios, taking into account privacy requirements and communication costs. Rather than...
Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
In the near future NASAintends to explore various regions of our solar systemusing robotic devices such as rovers, spacecraft, airplanes, and/or balloons. Such platforms will carr...
Jonathan J. Oliver, Ted Roush, Paul Gazis, Wray L....
Associative classification, which originates from numerical data mining, has been applied to deal with text data recently. Text data is firstly digitalized to database of transact...
Baoli Li, Neha Sugandh, Ernest V. Garcia, Ashwin R...