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