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Knowledge Discovery and Data Mining (KDD) is a very wellestablished research eld with useful techniques that explore patterns and regularities in large relational, structured and unstructured datasets. Theoretical and practical development in this eld have led to useful and scalable solutions for the tasks of pattern mining, clustering, graph mining, and predictions. In this paper, we demonstra...

We approach the challenging problem of discovering influences between painters based on their fine-art paintings. In this work, we focus on comparing paintings of two painters in terms of visual similarity. This comparison is fully automatic and based on computer vision approaches and machine learning. We investigated different visual features and similarity measurements based on two different ...

Both, the number and the size of spatial databases, such as geographic or medical databases, are rapidly growing because of the large amount of data obtained from satellite images, computer tomography or other scientific equipment. Knowledge discovery in databases (KDD) is the process of discovering valid, novel and potentially useful patterns from large databases. Typical tasks for knowledge d...

In this paper, we indicate some possible applications of ILP or similar techniques in the knowledge discovery eld, and then discuss several methods for adapting and linking ILP-systems to relational database systems. The proposed methods range from \pure ILP" to \based on techniques originating in ILP". We show that it is both easy and advantageous to adapt ILP-systems in this way.

Actionable Association Rule mining (AAR) is a closed optimization problem solving process from problem definition, model design to actionable pattern discovery, and is designed to deliver apt business rules that can be integrated with business processes and technical aspects. To support such processes, we correspondingly propose, formalize and illustrate a generic AAR model design: Multisource ...

In this paper we describe two systems designed to connect users to distributed, continuously changing experts and their knowledge. Using information retrieval, information extraction, and collaborative filtering techniques, these systems are able to enhance corporate knowledge management by overcoming traditional problems of knowledge acquisition and maintenance and associated (human and financ...

Digital libraries allow us to organize a vast amount of publications in a structured way and to extract information of user’s interest. In order to support customized use of digital libraries, we develop novel methods and techniques in the Knowledge Discovery in Scientific Literature (KDSL) research program of our graduate school. It comprises several sub-projects to handle specific problems in...

This book presents recent advances in Knowledge discovery in databases (KDD) with a focus on the areas of market basket database, time-stamped databases. Outline. 1 Knowledge Discovery in Databases. Introduction. Definitions of KDD. 2 The KDD process. Steps of KDD. Discovery goals. Mining Methodologies. Knowledge discovery in databases (KDD) is an important activity, and require only to process...