DocumentCode :
845489
Title :
From unstructured data to actionable intelligence
Author :
Rao, Ramana
Author_Institution :
inxight, Sunnyvale, CA, USA
Volume :
5
Issue :
6
fYear :
2003
Firstpage :
29
Lastpage :
35
Abstract :
There´s content everywhere, but not the information you need. Content analysis can organize a pile of text into a richly accessible repository. This article explains two key technologies for generating metadata about content - automatic categorization and information extraction. These technologies, and the applications that metadata makes possible, can transform an organization´s reservoir of unstructured content into a well-organized repository of knowledge. With metadata available, a company´s search system can move beyond simple dialogs to richer means of access that work in more situations. Information visualization, for example, uses metadata and our innate visual abilities to improve access. Besides better access, metadata enables intelligent switching in the content flows of various organizational processes - for example, making it possible to automatically route the right information to the right person. A third class of metadata applications involves mining text to extract features for analysis using the statistical approaches typically applied to structured data. For example, if you turn the text fields in a survey into data, you can then analyze the text along with other data fields. All these metadata-powered applications can improve your company´s use of its information resources.
Keywords :
computational linguistics; data mining; data visualisation; database management systems; information management; meta data; text analysis; accessible repository; actionable intelligence; automatic categorization; content analysis; content flows; content generation; feature extraction; information extraction; information resources; information routing; information visualization; intelligent switching; metadata generation; metadata-powered applications; search system; statistical analysis; structured data; text analysis; text mining; unstructured data; Art; Costs; Data mining; Electronic mail; Knowledge management; Libraries; Productivity; Proposals; Reservoirs; Taxonomy;
fLanguage :
English
Journal_Title :
IT Professional
Publisher :
ieee
ISSN :
1520-9202
Type :
jour
DOI :
10.1109/MITP.2003.1254966
Filename :
1254966
Link To Document :
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