Knowledge Discovery in Databases (KDD) is a relatively new field of research. Interest generated by KDD has been huge. International companies are looking to KDD techniques to maximise profit and enhance decision support. The aim of this paper is to provide an overview and understanding of the ideas, techniques and applications found within this field.

• Mining Uncertain Heterogenous Information Networks Scalable and intelligent methods to handle the challenges of uncertainty, heterogeneity, and large volumes and/or low bandwidth, focused on three major data sources in military. network + spatial-temporal data + streams. • Domain Integration for Decision Support Integrate knowledge learned from networks, spatial-temporal data and streams all ...

Within large corpora of texts, Knowledge-Rich Contexts (KRCs) are a subset of sentences containing information that would be valuable to a human for the construction of a knowledge base. The entry point to the discovery of KRCs is the automatic identification of Knowledge Patterns (KPs) which are indicative of semantic relations. Machine readable dictionary serves as our starting point for inve...

Reading a book is also kind of better solution when you have no enough money or time to get your own adventure. This is one of the reasons we show the scientific data mining and knowledge discovery principles and foundations as your friend in spending the time. For more representative collections, this book not only offers it's strategically book resource. It can be a good friend, really good f...

Recent papers have shown that, in contrast to ―the Long Tail‖ theory, movie sales remain concentrated in a small number of hits. These papers have argued that concentrated sales can be explained, in part, by heterogeneity in quality and increasing returns from social effects. Our research analyzes an additional explanation: how incomplete information may skew sales patterns. We use the movie br...

This paper surveys the growing number of indu5 trial applications of data mining and knowledge discovery. We look at the existing tools, describe some representative applications, and discuss the major issues and problems for building and deploying successful applications and their adoption by business users. Finally, we examine how to assess the potential of a knowledge discovery application.

Driven by the need for transparent discovery and orchestration of composite services out of elementary services, this paper introduces an innovative approach to Distributed Composite Services Orchestration and Discovery. The proposed concept is based on Variant Configuration theory and Distributed Service Repositories. The authors proceed to describe parts of the specification of a middleware p...

In contrast with traditional modelling methods, which are used to identify parameter values of a model with known structure, equation discovery systems identify the structure of the model also. The model generated with such systems can give experts a better insight into the measured data and can be also used for predicting future values of the measured variables. This paper presents LAGRAMGE, a...

Knowledge Management is a discipline with many faces – among very provocative ones is the research area dealing with automatic discovery of the hidden truth within the data describing the world around us. The basic idea of knowledge discovery is to let the computer search for the knowledge whereas the humans give just broad directions about where and how to search. Surprisingly, it is often the...