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Publication Detailed Description
2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): Proceedings
Year (definitive publication)
2014
Language
English
Country
United States of America
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Abstract
In this paper we propose to approach the subject of Twitter Topic Detection using a new technique called Topic
Fuzzy Fingerprints. A comparison is made with two popular text classification techniques, Support Vector Machines (SVM) and k-Nearest Neighbours (kNN). Preliminary results show that Twitter Topic Fuzzy Fingerprints outperforms the other two techniques achieving better Precision and Recall, while still being
much faster, which is an essential feature when processing large volumes of streaming data.
Acknowledgements
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Keywords
Fields of Science and Technology Classification
- Physical Sciences - Natural Sciences
Funding Records
| Funding Reference | Funding Entity |
|---|---|
| PEstOE/EEI/LA0021/2013 | Fundação para a Ciência e a Tecnologia |
| PTDC/IVC-ESCT/4919/2012 | Fundação para a Ciência e a Tecnologia |
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