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Intelligent Data Analysis
The size and variety of machine-readable data sets have increased dramatically and the problem of “data explosion” has become apparent. On the other hand, recent developments in computing have provided the basic infrastructure for fast data access as well as many advanced computational methods for extracting information from large quantities of data. These developments have created a new range of problems and challenges for data analysts as well as new opportunities for intelligent systems in data analysis, and have led to the emergence of the field of Intelligent Data Analysis (IDA).
IDA is an interdisciplinary study concerned with the effective analysis of data, which draws the techniques from diverse fields including artificial intelligence, databases, high-performance computing, pattern recognition and statistics. These fields often complement each other, e.g. many statistical methods, particularly those for large data sets, rely on computation, but brute computing power is no substitute for statistical knowledge.
In response to the challenge of extracting useful information from large quantities of on-line data from emerging areas such as bioinformatics and systems biology, many interesting IDA systems and applications have been built and a better understanding of the IDA principles has been obtained over the last decade or so. However, there remain many important but difficult issues in the field.
The goal of this workshop is to bring together a number of researchers from statistics, machine learning, computer science, pattern recognition, bioinformatics, systems biology and other areas to discuss important issues in IDA, review current progress in the field, and identify those challenging and fruitful areas for further research. The workshop is intended to stimulate interaction between these different areas, so that more powerful tools can emerge for extracting knowledge from data and a better understanding is developed of the process of intelligent data analysis. In particular we would like to focus on the following key issues from both application and theoretical viewpoints:
Since this is an interdisciplinary meeting we believe that the initiation of fruitful interactions across different disciplines is the key to the successful running of the workshop. In this regard we will plan several ice-breaking activities such as arranging introductory tutorial-style presentations, aiming to familiarize researchers with concepts from the various fields; inviting data owners to describe challenging biomedical applications, particularly those related to high-throughput bioinformatics. Participants of the workshop will also be invited beforehand to tackle some challenging biological data analysis problems, e.g. in DNA or Protein microarray areas so that various approaches can be discussed and compared during the workshop.