In this paper we propose a meta-modeling approach to adaptive knowledge management. It extends previous work by introducing an application-specific layer which allows to specify m...
Data stream applications have made use of statistical summaries to reason about the data using nonparametric tools such as histograms, heavy hitters, and join sizes. However, rela...
Rapid developments in digital technologies have brought to force new challenges in innovation. In this paper, we propose a taxonomic framework of innovation networks in order to i...
Youngjin Yoo, Kalle Lyytinen, Richard J. Boland Jr...
The goal of conceptual clustering is to build a set of embedded classes, which cluster objects based on their similarities. Knowledge organization aims at generating the set of mos...
Nearest neighborhood consistency is an important concept in statistical pattern recognition, which underlies the well-known k-nearest neighbor method. In this paper, we combine th...