Traditional methods for frequent itemset mining typically assume that data is centralized and static. Such methods impose excessive communication overhead when data is distributed...
Matthew Eric Otey, Chao Wang, Srinivasan Parthasar...
This paper proposes a data mining approach to modeling relationships among categories in image collection. In our approach, with image feature grouping, a visual dictionary is cre...
Share-frequent pattern mining discovers more useful and realistic knowledge from database compared to the traditional frequent pattern mining by considering the non-binary frequen...
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
Several randomized techniques have been proposed for privacy preserving data mining of continuous data. These approaches generally attempt to hide the sensitive data by randomly m...