Song, Dawei; Bruza, Peter; Huang, Helen and Lau, Raymond
(2003).
| DOI (Digital Object Identifier) Link: | http://dx.doi.org/doi:10.1007/b14019 |
|---|---|
| Google Scholar: | Look up in Google Scholar |
Abstract
We propose an intelligent document title classification agent based on a theory of information inference. The information is represented as vectorial spaces computed by a cognitively motivated model, namely Hyperspace Analogue to Language (HAL). A combination heuristic is used to combine a group of concepts into one single combination vector. Information inference can be performed on the HAL spaces via computing information flow between vectors or combination vectors. Based on this theory, a document title is treated as a combination vector by applying the combination heuristic to all the non-stop terms in the title. Two methodologies for learning and assigning categories to document titles are addressed. Experimental results on Reuters-21578 corpus show that our framework is promising and its performance achieves 71% of the upper bound (which is approximated by using whole documents).
| Item Type: | Book Chapter |
|---|---|
| ISBN: | 3-540-20256-0, 978-3-540-20256-1 |
| Academic Unit/Department: | Mathematics, Computing and Technology > Computing Knowledge Media Institute |
| Item ID: | 9331 |
| Depositing User: | Users 6898 not found. |
| Date Deposited: | 28 Sep 2007 |
| Last Modified: | 22 Jun 2012 11:35 |
| URI: | http://oro.open.ac.uk/id/eprint/9331 |
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