Special Issue "Intelligent Data Analysis"
A special issue of Information (ISSN 2078-2489).
Deadline for manuscript submissions: closed (20 December 2014).
Intelligent Data Analysis (IDA) is one of the hot issues in the field of artificial intelligence and information. Intelligent data analysis reveals implicit, previously unknown and potentially valuable information or knowledge from large amounts of data. Intelligent data analysis is also a kind of decision support process. Based on artificial intelligence, machine learning, pattern recognition, statistics, database and visualization technology mainly, IDA automatically extracts useful information, necessary knowledge and interesting models from a lot of online data in order to help decision makers make the right choices.
The process of IDA generally consists of the following three stages: (1) data preparation; (2) rule finding or data mining; (3) result validation and explanation. Data preparation involves selecting the required data from the relevant data source and integrating this into a data set to be used for data mining. Rule finding is working out rules contained in the data set by means of certain methods or algorithms. Result validation requires examining these rules, and result explanation is giving intuitive, reasonable and understandable descriptions using logical reasoning.
As the goal of intelligent data analysis is to extract useful knowledge, the process demands a combination of extraction, analysis, conversion, classification, organization, reasoning, and so on. It is challenging and fun working out how to choose appropriate methods to resolve the difficulties encountered in the process. Intelligent data analysis methods and tools, as well as the authenticity of obtained results pose us continued challenges.
The goal of this Special Issue is to provide the interested reader with a collection of papers describing recent developments in intelligent data analysis. Topics of interest include, but are not limited to:
- Theory and model
- Algorithm and simulation
- Feature extraction
- Parallel and distributed data analysis
- Big data analysis
- Image analysis
- Multimedia analysis
- Complex data analysis
- Web information analysis
- Economic data analysis
- Biomedical data analysis
- Medical informatics
Prof. Dr. Min Yao
Manuscript Submission Information
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