ADMRG @ MediaEval 2013 Social Event Detection


Autoria(s): Sutanto, Taufik; Nayak, Richi
Contribuinte(s)

Reuter, Timo

Larson, Martha

Data(s)

23/10/2013

Resumo

This paper elaborates the approach used by the Applied Data Mining Research Group (ADMRG) for the Social Event Detection (SED) Tasks of the 2013 MediaEval Benchmark. We extended the constrained clustering algorithm to apply to the first semi-supervised clustering task, and we compared several classifiers with Latent Dirichlet Allocation as feature selector in the second event classification task. The proposed approach focuses on scalability and efficient memory allocation when applied to a high dimensional data with large clusters. Results of the first task show the effectiveness of the proposed method. Results from task 2 indicate that attention on the imbalance categories distributions is needed.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/63821/

Publicador

CEUR-WS.org

Relação

http://eprints.qut.edu.au/63821/1/ADMRG-QUT_MediaEval_SED_2013.pdf

http://ceur-ws.org/Vol-1043/mediaeval2013_submission_38.pdf

Sutanto, Taufik & Nayak, Richi (2013) ADMRG @ MediaEval 2013 Social Event Detection. In Reuter, Timo & Larson, Martha (Eds.) Proceedings of the MediaEval 2013 Multimedia Benchmark Workshop, CEUR-WS.org, Barcelona, Spain.

Direitos

Copyright 2013 The Authors

Fonte

School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #080109 Pattern Recognition and Data Mining #Constrained Clustering #Social Event Detection #Ranking #Document Clustering
Tipo

Conference Paper