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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Cambria, E. Hussain, A. Durrani, T. Havasi, C. Eckl, C. Munro, J. |
| Copyright Year | 2010 |
| Description | Author affiliation: Dept. of Computing Science and Mathematics, University of Stirling, Stirling, FK9 4LA, UK; MIT Media Lab, MIT, Cambridge, MA 02142-1323, USA; Sitekit Labs, Sitekit Solutions Ltd., Portree, IV51 9HL, UK; Patient Opinion, Sheffield, S3 8EN, UK (Cambria, E.; Hussain, A.; Durrani, T.; Havasi, C.; Eckl, C.; Munro, J.) |
| Abstract | Next-generation patients are far from being peripheral to health-care. They are central to understanding the effectiveness and efficiency of services and how they can be improved. Today a lot of patients are used to reviewing local health services on-line but this social information is just stored in natural language text and it is not machine-accessible and machine-processable. To distil knowledge from this extremely unstructured information we use Sentie Computing, a new opinion mining and sentiment analysis paradigm which exploits AI and Semantic Web techniques to better recognize, interpret and process opinions and sentiments in natural language text. In particular, we use a language visualization and analysis system, a novel emotion categorization model, a resource for opinion mining based on a web ontology and novel techniques for finding and defining topic dependent concepts, namely spectral association and CF-IOF weighting respectively. |
| Starting Page | 1279 |
| Ending Page | 1282 |
| File Size | 182834 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424458974 |
| e-ISBN | 9781424459001 |
| DOI | 10.1109/ICOSP.2010.5657072 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-10-24 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Hospitals Natural languages Semantics Approximation methods XML Analytical models Databases E-Health AI Semantic Networks Knowledge Base Management NLP Opinion Mining and Sentiment Analysis |
| Content Type | Text |
| Resource Type | Article |
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