In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
The current technologies have made it possible to execute parallel applications across heterogeneous platforms. However, the performance models available do not provide adequate m...
Jameela Al-Jaroodi, Nader Mohamed, Hong Jiang, Dav...
Automatic metadata generation provides scalability and usability for digital libraries and their collections. Machine learning methods offer robust and adaptable automatic metadat...
Hui Han, C. Lee Giles, Eren Manavoglu, Hongyuan Zh...
This paper presents a seed placement strategy for streamlines based on flow features in the dataset. The primary goal of our seeding strategy is to capture flow patterns in the ...
We present new parallel algorithms for 3D reconstruction of objects from 2D projections and their application for the determination of the structure of macromolecules from electro...
Robert E. Lynch, Dan C. Marinescu, Hong Lin, Timot...