@article{(Open Science Index):https://publications.waset.org/pdf/4457,
	  title     = {Powerful Tool to Expand Business Intelligence: Text Mining},
	  author    = {Li Gao and  Elizabeth Chang and  Song Han},
	  country	= {},
	  institution	= {},
	  abstract     = {With the extensive inclusion of document, especially
text, in the business systems, data mining does not cover the full
scope of Business Intelligence. Data mining cannot deliver its impact
on extracting useful details from the large collection of unstructured
and semi-structured written materials based on natural languages.
The most pressing issue is to draw the potential business intelligence
from text. In order to gain competitive advantages for the business, it
is necessary to develop the new powerful tool, text mining, to expand
the scope of business intelligence.
In this paper, we will work out the strong points of text mining in
extracting business intelligence from huge amount of textual
information sources within business systems. We will apply text
mining to each stage of Business Intelligence systems to prove that
text mining is the powerful tool to expand the scope of BI. After
reviewing basic definitions and some related technologies, we will
discuss the relationship and the benefits of these to text mining. Some
examples and applications of text mining will also be given. The
motivation behind is to develop new approach to effective and
efficient textual information analysis. Thus we can expand the scope
of Business Intelligence using the powerful tool, text mining.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {1},
	  number    = {8},
	  year      = {2007},
	  pages     = {2666 - 2671},
	  ee        = {https://publications.waset.org/pdf/4457},
	  url   	= {https://publications.waset.org/vol/8},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 8, 2007},