Mining from Data Streams: Issues and Challenges
Speaker: Dr Joao Gama, University of Porto, Portugal
When: 2009-08-24 15:00:00
Venue: 78-420
Host: Dr Xue Li
Abstract:The Machine Learning community is faced to new challenges with the advent of sources producing continuously flow of data. Examples of streaming data include sensor networks, customer click streams, telephone records, web logs, multimedia data, sets of retail chain transactions, etc. These data sources are characterized by high-speed flow of huge amounts of data generated from non stationary distributions. In consequence, new learning techniques are needed to process streaming data in reasonable time and space. The goal of this tutorial is to present and discuss the research problems, issues and challenges in learning from data streams. We will present the state-of-the-art techniques in change detection, clustering, classification, frequent patterns, and time series analysis from data streams. We will discuss the current trends, challenges and open issues and future directions in learning from data streams, Specific goals and objectives:
Introducing the area of data stream mining Giving a detailed explanation of the major techniques in the area Emphasizing the open research issues and challenges
Biography:Joao Gama is a researcher at LIAAD-INESC Porto LA, the Laboratory of Artificial Intelligence and Decision Support of the University of Porto.
His main research interest is Learning from Data Streams. He has published several articles in change detection, learning decision trees from data streams, hierarchical clustering from streams, etc. Editor of special issues on Data Streams in Intelligent Data Analysis, J. Universal Computer Science, and New Generation Computing.
Co-chair of ECML 2005 Porto, ADMA 2009, Beijing, Discovery Science 2009, Porto, and of a series of Workshops on Knowledge Discovery in Data Streams, in conjunction with ECML-PKDD (2004, 2005, 2006, 2007, 2008) and ICML 2006, ACM Symposium on Applied Computing in 2007, 2008, 2009, 2010, and the ACM Workshop on Knowledge Discovery from Sensor Data, held in conjunction with ACM SIGKDD 2007, 2008, 2009.
Together with M. Gaber edited the book Learning from Data Streams-Processing Techniques in Sensor Networks, published by Springer.
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Contact:Dr Xue Li