Title :
Twitter Topic Fuzzy Fingerprints
Author :
Rosa, Hugo ; Batista, F. ; Carvalho, Jose P.
Author_Institution :
Inst. Super. Tecnico, Univ. de Lisboa, Lisbon, Portugal
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 fc-Nearest Neighbours (fcNN). 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.
Keywords :
data mining; fuzzy set theory; media streaming; pattern classification; social networking (online); support vector machines; text analysis; SVM; Twitter topic detection; Twitter topic fuzzy fingerprints; k-nearest neighbours; kNN; streaming data processing; support vector machine; text classification technique; Fingerprint recognition; Libraries; Market research; Support vector machines; Training; Twitter;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-2073-0
DOI :
10.1109/FUZZ-IEEE.2014.6891781
