In this paper, we propose a novel data mining technique for the efficient damage detection within the large-scale complex mechanical structures. Every mechanical structure is defi...
Aleksandar Lazarevic, Ramdev Kanapady, Chandrika K...
We present a graph-theoretic approach to discover storylines from search results. Storylines are windows that offer glimpses into interesting themes latent among the top search re...
Part numbers are widely used within an enterprise throughout the manufacturing process. The point of entry of such part numbers into this process is normally via a Bill of Materia...
Detection of space-time clusters is an important function in various domains (e.g., epidemiology and public health). The pioneering work on the spatial scan statistic is often use...
World steel trade becomes more competitive every day and new high international quality standards and productivity levels can only be achieved by applying the latest computational...
Clustering time series is a problem that has applications in a wide variety of fields, and has recently attracted a large amount of research. In this paper we focus on clustering...
One of the classic data mining problems is discovery of frequent itemsets. This problem particularly attracts database community as it resembles traditional database querying. In t...
Maciej Zakrzewicz, Mikolaj Morzy, Marek Wojciechow...
Facilitated by the achievements of various data mining techniques, both academic research and industrial applications are using data mining tools to explore knowledge from various ...
Vehicle production audit tests, warranty claims and car control unit data are stored in a central data warehouse for data mining analysis. Neural network based part failure rate es...
Matthias Grabert, Markus Prechtel, Tomas Hrycej, W...