DM 2014 - Special Track at Data Mining (DM), David Bisant and William Eberle

What is Data Mining?
Data mining is the process of extracting hidden patterns from data. As more data is gathered, data mining is becoming an increasingly important tool to transform this data into information. It is commonly used in a wide range of profiling services, such as marketing, surveillance, fraud detection and scientific discovery (http://en.wikipedia.org/wiki/Data_mining).
What is the GOAL of the track?
This special track will be devoted to data mining with the aim of presenting new and important contributions in this area.
Who might be interested?
Papers and contributions are encouraged for any work related to Data Mining.
What kind of studies will be of interest?
Topics of interest may include (but are in no way limited to):
1. Applications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, intrusion detection, remote sensing, earth sciences, bioinformatics, and astronomy.
2. Modeling algorithms such as hidden Markov models, decision trees, neural networks, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches.
3. Feature extraction and selection.
4. Post-processing techniques such as visualization, summarization, or trending.
5. Preprocessing and data reduction.
6. Knowledge engineering or warehousing.
Note: We invite original papers (i.e. work not previously submitted, in submission, or to be submitted to another conference during the reviewing pro