Model reduction is an important systems task with a long history in traditional chemical engineering modeling. We discuss its interplay with modern data-mining tools (such as Local Feature Analysis and Diffusion Maps) through illustrative examples, and comment on important open issues regarding applications to large systems arising in molecular/atomistic simulations.

Résumé. L’informatique décisionnelle est un secteur en forte croissance dans toutes les entreprises. Les techniques classiques (reporting simple & Olap), qui s’intéressent essentiellement à présenter les données, sont aujourd’hui très largement déployées. Le data mining commence à se répandre, apportant des capacités de prévision à forte valeur ajoutée pour les entreprises les plus compétitives...

Mining opinion leaders is of great significance to the dissemination of information in social network. This paper put forward a mining algorithm of opinion leaders in social network. First, the algorithm defined the concept of attention degree based on the analysis of user attention behaviors including forward, comment, point praise and other concerns. Then it adopted the ideas of voting in the...

This paper is an overview of a Data Mining project carried out by the Warsaw University of Technology in the Network Planning and Maintenance Department of a Polish cellular telecom provider. This project has provided an excellent opportunity to test various Data Mining methods on real, non-classic (i.e. mostly not related to purely marketing problems) data from the technology area. In this pap...

T he prevalence of imageand videocapturing devices and the advent of media-sharing services such as Flickr and YouTube have drastically increased the volume of community-contributed multimedia. For example, there are reportedly more than four billion images in Flickr and 24 hours of new videos are uploaded to YouTube every minute. Such a vast amount of photos, videos, and music shared via websi...

The ability to manage faults in large scale networks is of vast importance for successful and eeective network management operations. In this paper, we describe FALCON, a project underway at AT&T Labs-Research focusing on fault management in IP networks. FALCON's goal is to automate various fault management tasks through warehousing and mining technologies. We describe FALCON's architecture and...

In spatial data mining, a common task is the discovery of spatial association rules from spatial databases. We propose a distributed system named ARES that assists data miners in the complex process of extracting the association rules from a spatial database. We also face a common problem of association rule mining, that is the high number of discovered rules. This affects both efficiency of th...

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