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Rosa, H., Batista, F. & Carvalho, J. (2014). Twitter topic fuzzy fingerprints. In 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): Proceedings. Beijing: IEEE.
H. Rosa et al., "Twitter topic fuzzy fingerprints", in 2014 IEEE Int. Conf. on Fuzzy Systems (FUZZ-IEEE): Proc., Beijing, IEEE, 2014
@inproceedings{rosa2014_1732225366059, 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" }
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 -