This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
An emerging class of data-intensive applications involve the geographically dispersed extraction of complex scientific information from very large collections of measured or compu...
William E. Allcock, Joseph Bester, John Bresnahan,...
There is a growing need, both for use within corporate intranets and within the rapidly evolving World Wide Web, to develop tools that are able to retrieve relevant textual inform...
L. J. Brown, Mariano P. Consens, Ian J. Davis, Chr...
— Most application data units are too large to be carried in a single packet (or cell) and must be segmented for network delivery. To an application, the end-to-end delays and lo...
An increasing number of applications use XML data published from relational databases. For speed and convenience, such applications routinely cache this XML data locally and acces...
Philip Bohannon, Sumit Ganguly, Henry F. Korth, P....