Challenges in Information Extraction from Text for Knowledge Management
(2001) Challenges in Information Extraction from Text for Knowledge Management. IEEE Intelligent Systems and Their Applications 16(6):84.
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Nowadays, most knowledge is stored in an unstructured textual format. We can’t query it in simple ways, thus automatic systems can’t use the contained knowledge and humans can’t easily manage it. The traditional knowledge management process for knowledge engineers has been to manually identify and extract knowledge—a complex and time-consuming process that requires a great deal of manual input. As an example consider the collection of interviews to experts (protocols) and their analysis by knowledge engineers in order to codify, model and extract the knowledge of an expert in a particular domain. In this context, information extraction from texts is one of the most promising areas of human language technology for KM applications.
| Keywords: | Knowledge management, information extraction |
|---|---|
| Subjects: | AKT Challenges > Knowledge acquisition |
| ID Code: | 126 |
| Deposited By: | Brewster, Christopher |
| Deposited On: | 27 February 2003 |
| Alternative Locations: | http://www.dcs.shef.ac.uk/~fabio/cira-papers.html |
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