In this paper we present the results of applying data mining techniques to identify patterns and anomalies in air traffic control operational errors (OEs). Reducing the OE rate is ...
In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...
: For the characteristics of malfunction diagnose system a model to classify fault printing based on support vector machines is discussed. The printing malfunctions have many class...
Autism spectrum disorder has become one of the most prevalent developmental disorders, characterized by a wide variety of symptoms. Many children need extensive therapy for years t...
Gondy Leroy, Annika Irmscher, Marjorie H. Charlop-...
: Data warehouse technology transforms the operational data store to general and compositive information. It also provides effective way for analysis and statistic to the mass data...
An approach to build a multi-class classifier is proposed in this paper. This approach consists of a derivation to show under which loss function an optimal classifier can be obtai...
We present an application of bi-dimensional and heterogeneous time series clustering in order to resolve a Social Sciences issue. The dataset is the result of a survey involving mo...
Segmentation is one of the fundamental components in time series data mining. One of the uses of the time series segmentation is trend analysis - to segment the time series into pr...
Abstract: Data preparation is a significant preprocessing task to prepare data for mining. The data mining process cannot succeed without a serious effort to prepare data. Very oft...
- With the growing usage of XML in the World Wide Web and elsewhere as a standard for the exchange of data and to represent semistructured data, there is an imminent need for tools...