We present a novel language for querying object-oriented databases. The language is built around the idea of extended path expressions that substantially generalize [ZAN83], and on an adaptation of the first-order formalization of object-oriented languages from [KW89, KLW90, KW92]. The language

■ Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. What is all the excitement about? This article provides an overview of this emerging field, clarifying how data mining and knowledge discovery

A large portion of real-world data is stored in commercial relational database systems. In contrast, most statistical learning methods work only with "flat " data representations. Thus, to apply these methods, we are forced to convert our data into a flat form, thereby losing much

Classification rule mining aims to discover a small set of rules in the database that forms an accurate classifier. Association rule mining finds all the rules existing in the database that satisfy some minimum support and minimum confidence constraints. For association rule mining, the target

-featured database systems and can answer only a small set of queries over their data (for example, forms on the WWW restrict the set of queries one can ask). (3) Since the number of sources is very large, effective techniques are needed to prune the set of information sources accessed to answer a query. (4

as two forms of data-based action synthesis “Do as I Do” and “Do as I Say”. Results are demonstrated on ballet, tennis as well as football datasets.

We describe a highly functional prototype system for searching by visual features in an image database. The VisualSEEk system is novel in that the user forms the queries by diagramming spatial arrangements of color regions. The system finds the images that contain the most similar arrangements

Emerging high-performance applications require the ability to exploit diverse, geographically distributed resources. These applications use high-speed networks to integrate supercomputers, large databases, archival storage devices, advanced visualization devices, and/or scientific instruments

and ap proximately 4000 findin nodes, with a number of ob served findings that varies per case. Due to the form of the noisy-or CPTs the complexity of inference is ex ponential in the number of positive findings Results Initial experiments The experimental protocol for the PYRAMID network was as follows

) and to two forms of stratification. Further tests identify the key components of MetaCost and those that can be varied without substantial loss. Experiments on a larger database indicate that MetaCost scales well.