@INPROCEEDINGS{1386Schmiedeke2012, AUTHOR = {Sebastian Schmiedeke and Pascal Kelm and Thomas Sikora}, TITLE = {TUB @ MediaEval 2012 Tagging Task: Feature Selection Methods for Bag-of-(visual)-Words Approaches}, BOOKTITLE = {Working Notes Proceedings of the MediaEval 2012 Workshop}, YEAR = {2012}, MONTH = oct, EDITOR = {Martha A. Larson, Sebastian Schmiedeke, Pascal Kelm, Adam Rae, Vasileios Mezaris, Tomas Piatrik, Mohammad Soleymani, Florian Metze, Gareth J.F. Jones}, PUBLISHER = {CEUR-WS.org}, PAGES = {79--80}, ADDRESS = {Santa Croce in Fossabanda Piazza Santa Croce, 5 - 56125 - Pisa - Toscana - Italia}, NOTE = {ISSN 1613-0073}, PDF = {http://elvera.nue.tu-berlin.de/files/1386Schmiedeke2012.pdf}, URL = {http://elvera.nue.tu-berlin.de/files/1386Schmiedeke2012.pdf}, ABSTRACT = {This paper describes our participation in the Genre Tagging Task of MediaEval 2012, which aims to predict the videos’ category label. In last year’s participation, we performed experiments with bag-of-words (BoW) approaches in which different constellations in respect of modalities, features, and methods were investigated. This year, we focus on feature selection methods to improve the classification performance in terms of mean average precision (mAP) and classification accuracy (CA). We investigated the effectiveness of selection methods based on scores calculated using mutual informa- tion (MI) or term frequency (TF) and the effectiveness of transformation methods like the principle component anal- ysis (PCA).} }