What is Data Mining?
<br>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).
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<br>What is the GOAL of the track?
<br>This special track will be devoted to data mining with the aim of presenting new and important contributions in this area.
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<br>Who might be interested?
<br>Papers and contributions are encouraged for any work related to Data Mining.
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<br>What kind of studies will be of interest?
<br>Topics of interest may include (but are in no way limited to):
<br>1. Applications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, ...
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What is Data Mining?
<br>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).
<br>
<br>What is the GOAL of the track?
<br>This special track will be devoted to data mining with the aim of presenting new and important contributions in this area.
<br>
<br>Who might be interested?
<br>Papers and contributions are encouraged for any work related to Data Mining.
<br>
<br>What kind of studies will be of interest?
<br>Topics of interest may include (but are in no way limited to):
<br>1. Applications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy.
<br>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.
<br>3. Feature extraction and selection.
<br>4. Post-processing techniques such as visualization, summarization, or trending.
<br>5. Preprocessing and data reduction.
<br>6. Knowledge engineering or warehousing.
<br>Papers dealing with Cloud-based unstructured data or Cloud-based tool suites, such as Mahout, are also encouraged.
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<br>Note: We invite original papers (i.e. work not previously submitted, in submission, or to be submitted to another conference during the reviewing process).
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<br>Submission Guidelines
<br>Interested authors should format their papers according to AAAI formatting guidelines. The papers should be original work (i.e., not submitted, in submission, or submitted to another conference while in review). Papers should not exceed 6 pages (or 4 pages for short paper, to be presented as a poster) and are due by November 17, 2014. For FLAIRS-28, the 2015 conference, the reviewing is a double blind process. Author names and affiliations should be X’d out on submitted papers to provide double-blind reviewing. Papers must be submitted as PDF through the EasyChair conference system, which can be accessed through the main conference web site (http://www.flairs-28.info/). Note: do not use a fake name for your EasyChair login - your EasyChair account information is hidden from reviewers. Authors should indicate the Data Mining special track for submissions. The proceedings of FLAIRS will be published by the AAAI. Authors of accepted papers will be required to sign a form transferring copyright of their contribution to AAAI. FLAIRS requires that there be at least one full author registration per paper.
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<br>Please, check the website http://www.flairs-28.info/ for further information.
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<br>Conference Proceedings
<br>Papers will be refereed and all accepted papers will appear in the conference proceedings, which will be published by AAAI Press.
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<br>Organizing Committee
<br>David Bisant, Central Security Svcs., bisant@umbc.edu
<br>William Eberle, Tennessee Technological University, weberle@tntech.edu
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