In this paper, we consider the evolution of structure within large online social networks. We present a series of measurements of two such networks, together comprising in excess ...
Measuring distance or some other form of proximity between objects is a standard data mining tool. Connection subgraphs were recently proposed as a way to demonstrate proximity be...
Many applications in text processing require significant human effort for either labeling large document collections (when learning statistical models) or extrapolating rules from...
In this paper we present a new approach to mining binary data. We treat each binary feature (item) as a means of distinguishing two sets of examples. Our interest is in selecting ...
Existing research on mining quantitative databases mainly focuses on mining associations. However, mining associations is too expensive to be practical in many cases. In this pape...
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent clo...
A new class of associations (polynomial itemsets and polynomial association rules) is presented which allows for discovering nonlinear relationships between numeric attributes wit...
Online stores providing subscription services need to extend user subscription periods as long as possible to increase their profits. Conventional recommendation methods recommend...
Time-series of count data are generated in many different contexts, such as web access logging, freeway traffic monitoring, and security logs associated with buildings. Since this...