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Export Reference (APA) 
Rosa, H., Batista, F. & Carvalho, J. (2014). Twitter topic fuzzy fingerprints. In 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): Proceedings. Beijing: IEEE.
Export Reference (IEEE) 
H. Rosa et al.,  "Twitter topic fuzzy fingerprints", in 2014 IEEE Int. Conf. on Fuzzy Systems (FUZZ-IEEE): Proc., Beijing, IEEE, 2014
Export BibTeX 
@inproceedings{rosa2014_1715938293134,
	author = "Rosa, H. and Batista, F. and Carvalho, J.",
	title = "Twitter topic fuzzy fingerprints",
	booktitle = "2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): Proceedings",
	year = "2014",
	editor = "",
	volume = "",
	number = "",
	series = "",
	doi = "10.1109/FUZZ-IEEE.2014.6891781",
	publisher = "IEEE",
	address = "Beijing",
	organization = "IEEE",
	url = "http://www.ieee-wcci2014.org"
}
Export RIS 
TY  - CPAPER
TI  - Twitter topic fuzzy fingerprints
T2  - 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): Proceedings
AU  - Rosa, H.
AU  - Batista, F.
AU  - Carvalho, J.
PY  - 2014
SN  - 1098-7584
DO  - 10.1109/FUZZ-IEEE.2014.6891781
CY  - Beijing
UR  - http://www.ieee-wcci2014.org
AB  - 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.

ER  -