Semantic labelling for document feature patterns using ontological subjects
Paper
Paper/Presentation Title | Semantic labelling for document feature patterns using ontological subjects |
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Presentation Type | Paper |
Authors | Tao, Xiaohui (Author), Li, Yuefeng (Author), Liu, Bin (Author) and Shen, Yan (Author) |
Editors | Zhong, Ning and Gong, Zhiguo |
Journal or Proceedings Title | Proceedings of the 2012 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2012) |
ERA Conference ID | 60342 |
Number of Pages | 5 |
Year | 2012 |
Place of Publication | Los Alamitos, CA. United States |
ISBN | 9780769548807 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/WI-IAT.2012.47 |
Web Address (URL) of Paper | http://www.fst.umac.mo/wic2012 |
Conference/Event | 2012 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2012) |
IEEE/WIC/ACM International Conference on Web Intelligence (WI) | |
Event Details | 2012 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2012) Event Date 04 to end of 07 Dec 2012 Event Location Macau, China |
Event Details | IEEE/WIC/ACM International Conference on Web Intelligence (WI) WI |
Abstract | Finding and labelling semantic features patterns of documents in a large, spatial corpus is a challenging problem. Text documents have characteristics that make semantic labelling difficult; the rapidly increasing volume of online documents makes a bottleneck in finding meaningful textual patterns. Aiming to deal with these issues, we propose an unsupervised documnent labelling approach based on semantic content and feature patterns. A world ontology with extensive topic coverage is exploited to supply controlled, structured subjects for labelling. An algorithm is also introduced to reduce dimensionality based on the study of ontological structure. The proposed approach was promisingly evaluated by compared with typical machine learning methods including SVMs, Rocchio, and kNN. |
Keywords | text classification; document patterns; ontology learning; feature selection; semantic labelling; pattern |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
460599. Data management and data science not elsewhere classified | |
461002. Human information behaviour | |
Public Notes | © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Byline Affiliations | Centre for Systems Biology |
Queensland University of Technology | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q1w6z/semantic-labelling-for-document-feature-patterns-using-ontological-subjects
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