This paper presents an overview of the motivation for, and the use of time-series data mining in, a Geospatial Decision Support System (GDSS). Our approach is based on a combinati...
Dan Li, Sherri K. Harms, Steve Goddard, William J....
- The KDD (Knowledge Discovery in Databases) paradigm is a step by step process for finding interesting patterns in large amounts of data. Data mining is one step in the process. T...
Frequency mining problem comprises the core of several data mining algorithms. Among frequent pattern discovery algorithms, FP-GROWTH employs a unique search strategy using compac...
It has long been noted that many data mining algorithms can be built on top of join algorithms. This has lead to a wealth of recent work on efficiently supporting such joins with ...
Lexiang Ye, Xiaoyue Wang, Dragomir Yankov, Eamonn ...
Abstract Data mining algorithms have been recently applied to software repositories to help on the maintenance of evolving software systems. In the past, information about what cla...
Lile Hattori, Gilson Pereira dos Santos Jr., Ferna...
Rare association rules are those that only appear infrequently even though they are highly associated with very specific data. In consequence, these rules can be very appropriate f...
The Cell Broadband Engine (CBE) is a new heterogeneous multi-core processor from IBM, Sony and Toshiba, and provides the potential to achieve an impressive level of performance for...
Abstract. One important challenge in data mining is to extract interesting knowledge and useful information for expert users. Since data mining algorithms extracts a huge quantity ...
Data mining is a useful decision support technique, which can be used to find trends and regularities in warehouses of corporate data. A serious problem of its practical applicatio...
Tadeusz Morzy, Marek Wojciechowski, Maciej Zakrzew...