DocumentCode
226932
Title
Twitter Topic Fuzzy Fingerprints
Author
Rosa, Hugo ; Batista, F. ; Carvalho, Jose P.
Author_Institution
Inst. Super. Tecnico, Univ. de Lisboa, Lisbon, Portugal
fYear
2014
fDate
6-11 July 2014
Firstpage
776
Lastpage
783
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4799-2073-0
Type
conf
DOI
10.1109/FUZZ-IEEE.2014.6891781
Filename
6891781
Link To Document