Automatic Concept Classification of Text From Electronic Meetings
| dc.contributor.author | Chen, Hsinchun | |
| dc.contributor.author | Hsu, P. | |
| dc.contributor.author | Orwig, Richard E. | |
| dc.contributor.author | Hoopes, L. | |
| dc.contributor.author | Nunamaker, Jay F. | |
| dc.date.accessioned | 2004-10-01T00:00:01Z | |
| dc.date.available | 2010-06-18T23:39:28Z | |
| dc.date.issued | 1994-10 | en_US |
| dc.date.submitted | 2004-10-01 | en_US |
| dc.identifier.citation | Automatic Concept Classification of Text From Electronic Meetings 1994-10, 37(10):56-73 Communications of the ACM | en_US |
| dc.identifier.uri | http://hdl.handle.net/10150/106084 | |
| dc.description | Artificial Intelligence Lab, Department of MIS, University of Arizona | en_US |
| dc.description.abstract | In this research we adopted an artificial intelligence (AI) approach to designing an automatic concept classification tool for electronic brainstorming output. The role of AI techniques such as machine learning and neural networks computing in groupware development can be significant. Through extensive content analysis, concept space generation, and neural network-based concept classification, our system can generate a tentative list of the important ideas and topics represented in meeting comments. Participants then can examine the systemâ s suggested list and the underlying comments. They can also revise or augment the list to produce their final consensus list. Allowing the system to act as an â intelligentâ aide for idea organization can alleviate some of the burdens of convergent tasks. | |
| dc.format.mimetype | application/pdf | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | ACM | en_US |
| dc.subject | Management Information Systems | en_US |
| dc.subject | Artificial Intelligence | en_US |
| dc.subject.other | National Science Digital Library | en_US |
| dc.subject.other | NSDL | en_US |
| dc.subject.other | Artificial intelligence lab | en_US |
| dc.subject.other | AI lab | en_US |
| dc.title | Automatic Concept Classification of Text From Electronic Meetings | en_US |
| dc.type | Journal Article (Paginated) | en_US |
| dc.identifier.journal | Communications of the ACM | en_US |
| refterms.dateFOA | 2018-06-23T22:00:28Z | |
| html.description.abstract | In this research we adopted an artificial intelligence (AI) approach to designing an automatic concept classification tool for electronic brainstorming output. The role of AI techniques such as machine learning and neural networks computing in groupware development can be significant. Through extensive content analysis, concept space generation, and neural network-based concept classification, our system can generate a tentative list of the important ideas and topics represented in meeting comments. Participants then can examine the systemâ s suggested list and the underlying comments. They can also revise or augment the list to produce their final consensus list. Allowing the system to act as an â intelligentâ aide for idea organization can alleviate some of the burdens of convergent tasks. |
