Data Mining in Business Research

Paper Summary:

This paper relates that the use of data mining, its adjunct technologies for text mining and the ability to interpret, analyze and create linguistic models from unstructured content is revolutionizing the concept of data mining away from being purely used for structured content in data warehouses to now encompass unstructured content found throughout organizations globally.
The paper then provides insights into various areas of data mining, and the currently high levels of growth analytics use and applications software are experiencing as a result.

Outline:
Executive Summary
Using Data Mining in Business Research
Exploring the principles of Data Mining in Business Research
Predictive Methods in Data Mining

From the Paper:

"A second predictive approach is called deviation detection. The purpose of this method is to discover the most significant changes in data from previously measured or median values. An example of the type of use for this predictive approach would be the development of strategies for selling tickets to frequent flyers who booked months in advance versus those that consistently book within a few weeks of their departure. A third approach to using data mining to predict future outcomes is using the classification approach, or technique. This predictive approach of classification uses a collection of records (training set) -- each record contains several attributes, one of them is the class (Ng & Han, 10). The task is to find a model for the class attribute as a function of other attributes, so, after that, previously unknown records can be assigned a very accurate class."

Sample of Sources Used:

• CoGenTex. Defining NLP in 2006. Retreived from the Internet on August 14, 2007 http://www.cogentex.com/technology/nlgintro.html
• Columbus, Louis. Blog Mining Gets Real. CRM Buyer Magazine and Website. Retrieved August 14, 2007. http://www.crmbuyer.com/story/43483.html
• Columbus and Murphy Re-orienting your content and knowledge management strategies. Louis Columbus and Jim Murphy. Report published October, 2002. AMR Research, Boston, MA
• ComputerWorld. Text Mining Mini Glossary. Published 2005. Retrieved August 14, 2007 from location: http://www.computerworld.com/databasetopics/data/story/0,10801,93967,00.html
• Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P., & Uthurusamy, R. Advances in knowledge discovery & data mining. Cambridge, MA: MIT Press. 1996. Chapters 3, 4, 5.

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