Abstract. Ecologists spend considerable effort integrating heterogeneous data for statistical analyses and simulations, for example, to run and test predictive models. Our research...
In this paper, we introduce a novel framework for clustering web data which is often heterogeneous in nature. As most existing methods often integrate heterogeneous data into a un...
GridRM is an open and extensible resource monitoring system, based on the Global Grid Forum's Grid Monitoring Architecture (GMA). GridRM is not intended to interact with appl...
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...
In a pervasive computing environment, one is facing the problem of handling heterogeneous data from different sources, transmitted over heterogeneous channels and presented on het...
In this paper we use a Unified Relationship Matrix (URM) to represent a set of heterogeneous data objects (e.g., web pages, queries) and their interrelationships (e.g., hyperlinks...
Wensi Xi, Edward A. Fox, Weiguo Fan, Benyu Zhang, ...
This paper considers the elements and challenges of heterogeneous data management and interdisciplinary collaboration, drawing from the literatures on participatory design, comput...
Karen S. Baker, Steven J. Jackson, Jerome R. Wanet...
Heterogeneous object co-clustering has become an important research topic in data mining. In early years of this research, people mainly worked on two types of heterogeneous data ...
A major problem in today's information-driven world is that sharing heterogeneous, semantically rich data is incredibly difficult. Piazza is a peer data management system tha...
Igor Tatarinov, Zachary G. Ives, Jayant Madhavan, ...