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Recent Advances In Data Mining Of Enterprise Data: Algorithms and Applications (Series on Computers and Operations Research) (Series on Computers and ... ... on Computers and Operations Research) [Hardcover]

T. Warren Liao , Evangelos Triantaphyllou

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Book Description

January 15, 2008 981277985X 978-9812779854
The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as enterprise data . The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making.


  • Enterprise Data Mining: A Review and Research Directions (T W Liao);
  • Application and Comparison of Classification Techniques in Controlling Credit Risk (L Yu et al.);
  • Predictive Classification with Imbalanced Enterprise Data (S Daskalaki et al.);
  • Data Mining Applications of Process Platform Formation for High Variety Production (J Jiao & L Zhang);
  • Multivariate Control Charts from a Data Mining Perspective (G C Porzio & G Ragozini);
  • Maintenance Planning Using Enterprise Data Mining (L P Khoo et al.);
  • Mining Images of Cell-Based Assays (P Perner);
  • Support Vector Machines and Applications (T B Trafalis & O O Oladunni);
  • A Survey of Manifold-Based Learning Methods (X Huo et al.); and other papers.

Product Details

More About the Author

Dr. Evangelos Triantaphyllou did all his graduate studies at Penn State University from 1984 to 1990. While at Penn State, he earned a Dual M.S. in Environment and Operations Research (OR) (in 1985), an M.S. in Computer Science (in 1988) and a Dual Ph.D. in Industrial Engineering and Operations Research (in 1990). His Ph.D. dissertation was related to data mining by means of optimization approaches. Since the spring of 2005 he is a Professor in the Computer Science Department at the Louisiana State University (LSU) in Baton Rouge, LA, U.S. Before that, he had served for 11 years as an Assistant, Associate, and Full Professor in the Industrial Engineering Department at the same university. He has also served for one year as an Interim Associate Dean for the College of Engineering at LSU.

His research is focused on decision-making theory and applications, data mining and knowledge discovery, and the interface of operations research and computer science. Since the years he was a graduate student, he has developed new methods for data mining and knowledge discovery and has also explored some of the most fundamental and intriguing subjects in decision making. In 1999 he has received the prestigious IIE (Institute of Industrial Engineers), OR Division, Research Award for his research contributions in the above fields. In 2005 he received an LSU Distinguished Faculty Award as recognition of his research, teaching, and service accomplishments. Some of his graduate students have also received awards and distinctions including the Best Dissertation Award at LSU for Science, Engineering and Technology for the year 2003.

In 2000 Dr. Triantaphyllou published a bestseller book on multi-criteria decision-making. Besides the previous monograph on decision making , he has co-edited two books. One on data mining by means of rule induction (2006) and another one on the mining of enterprise data (2008). In the summer of 2010 he published a monograph on data mining and knowledge discovery by means of logic-based methods.

He always enjoys doing research with his students from which he has learned / learning a lot. He has received teaching awards and distinctions. His research has been funded by federal and state agencies, and the private sector. He has extensively published in some of the top refereed journals and made numerous presentations in national and international conferences.

Dr. Triantaphyllou has a strong inter-disciplinary background. He has always enjoyed organizing multi-disciplinary teams of researchers and practitioners with complementary expertise. These groups try to comprehensively attack some of the most urgent problems in the sciences and engineering. He is a strong believer of the premise that the next round of major scientific and engineering discoveries will come from the work of such inter-disciplinary groups. More details of his work can be found in his web site ( ).

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