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A smarter process for sensing the information space

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7 Author(s)

As a result of the growth of the Internet, the amount of available information is exponentially increasing. However, increasing the amount of information does not imply increasing usefulness. Furthermore, as the complexity of business relationships increases, there is a natural tendency toward less structured interaction between entities. This highlights the growing relevance of unstructured information in documenting the interactions of organizations and individuals. Analyzing and making sense of this unstructured information space requires more than text-mining algorithms; it requires a strategic approach. We propose a unified approach that addresses a variety of information space analytics problems. Our method for making sense of unstructured data is described by six steps that are analogous to the algebraic order of operations PEMDAS (parenthesis, exponent, multiplication, division, addition, and subtraction). These basic text-mining operations can be combined in many interesting ways to handle a diverse set of problems, and just as in algebra, it is critical that these operations be performed in the correct order to guarantee a meaningful result. In this paper, we describe how PEMDAS has been implemented within organizations to enable decisions that produced measurable business value.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Journal of Research and Development  (Volume:54 ,  Issue: 4 )

Date of Publication:

July-Aug. 2010

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