Encyclopedia of Data Warehousing and Mining

13 May 2009 |

There has been much interest developed in the data mining field both in the academia and the industry over the past 10-15 years. The number of researchers and practitioners working in the field and the number of scientific papers published in various data mining outlets increased drastically over this period. Major commercial vendors incorporated various data mining tools into their products, and numerous applications in many areas, including life sciences, finance, CRM, and Web-based applications, have been developed and successfully deployed.

Moreover, this interest is no longer limited to the researchers working in the traditional fields of statistics, machine learning and databases, but has recently expanded to other fields, including operations research/management science (OR/MS) and mathematics, as evidenced from various data mining tracks organized at different INFORMS meetings, special issues of OR/MS journals and the recent conference on Mathematical Foundations of Learning Theory organized by mathematicians.

As the Encyclopedia of Data Warehousing and Mining amply demonstrates, all these diverse interests from different groups of researchers and practitioners helped to shape data mining as a broad and multi-faceted discipline spanning a large class of problems in such diverse areas as life sciences, marketing (including CRM and e-commerce), finance, telecommunications, astronomy, and many other fields (the so called “data mining and X” phenomenon, where X constitutes a broad range of fields where data mining is used for analyzing the data). This also resulted in a process of cross-fertilization of ideas generated by these diverse groups of researchers interacting across the traditional boundaries of their disciplines.

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