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Bag-of-Genres for Video Genre Retrieval [article]

Leonardo A. Duarte, Otávio A. B. Penatti, Jurandy Almeida
2015 arXiv   pre-print
Therefore, it is interesting to encode the distribution of such genres in a compact and effective manner. We propose to create a visual dictionary using a genre classifier.  ...  We evaluate the bag-of-genres model for video genre retrieval, using the dataset of MediaEval Tagging Task of 2012.  ...  It is interesting to note the differences in responsiveness of the different approaches with respect to each of the genres.  ... 
arXiv:1506.00051v1 fatcat:hhhjgrhmmnc27cnz6mr7okzwlm

Learning to classify documents according to genre

Aidan Finn, Nicholas Kushmerick
2006 Journal of the American Society for Information Science and Technology  
We further combine predictions from different feature-sets to selectively sample which documents to add to the training set and show that this approach improves the learning rate of the resulting genre  ...  Domain transfer indicates the ability of a genre classifier to classify documents that are about topics other than those it was trained on.  ...  Acknowledgements This research was funded by Science Foundation Ireland and the US Office of Naval Research. Thanks to Barry Smyth for his advice and assistance on this project.  ... 
doi:10.1002/asi.20427 fatcat:yacnvdmwjvd53c3bsx3lqwzjui

Automatic music genre classification using ensemble of classifiers

Carlos N. Silla Jr., Celso A. A. Kaestner, Alessandro L. Koerich
2007 2007 IEEE International Conference on Systems, Man and Cybernetics  
This paper presents a novel approach to the task of automatic music genre classification which is based on multiple feature vectors and ensemble of classifiers.  ...  Individual classifiers are trained to account for each feature vector extracted from each music segment.  ...  However, this approach is not reliable since the classification of different parts of a music piece can lead to different classification outputs and different error rates.  ... 
doi:10.1109/icsmc.2007.4414136 dblp:conf/smc/SillaKK07 fatcat:fajtcu6lqbeozjv26xc33b2fwe

MediaEval 2018 AcousticBrainz Genre Task: A Baseline Combining Deep Feature Embeddings Across Datasets

Sergio Oramas, Dmitry Bogdanov, Alastair Porter
2018 MediaEval Benchmarking Initiative for Multimedia Evaluation  
In this paper we present a baseline approach for the MediaEval 2018 AcousticBrainz Genre Task that takes advantage of stacking multiple feature embeddings learned on individual genre datasets by simple  ...  Although we employ basic neural networks, the combination of their deep feature embeddings provides a significant gain in performance compared to each individual network.  ...  Economy and Competitiveness of the Spanish Government (Reference: TIN2015-69935-P).  ... 
dblp:conf/mediaeval/OramasBP18 fatcat:6zcukwx64benthx2sh7b5xrwbi

Bayes-Optimal Hierarchical Multilabel Classification

Wei Bi, Jame T. Kwok
2015 IEEE Transactions on Knowledge and Data Engineering  
We utilize a hierarchical set of multilabel classifiers to predict genres and subgenres and rely on a voting scheme to predict labels across datasets.  ...  This paper summarizes our contribution (team DBIS) to the Acous-ticBrainz Genre Task: Content-based music genre recognition from multiple sources as part of MediaEval 2017.  ...  -therest strategy, effectively training a separate binary classifier for every label. Different genre labels across data sets.  ... 
doi:10.1109/tkde.2015.2441707 fatcat:q7wzvifruzhztf5agozmjyez7m

Selection of Training Instances for Music Genre Classification

Miguel Lopes, Fabien Gouyon, Alessandro L. Koerich, Luiz E.S. Oliveira
2010 2010 20th International Conference on Pattern Recognition  
The particularity of our approach lies in a pre-classification of instances prior to the main classifier training: i.e. we select from the training data those instances that show better discrimination  ...  The objective is to build, from only a portion of the training data, a music genre classifier with at least similar performance as when the whole data is used.  ...  The particularity of our approach lies in a process of instance selection prior to classifier training: i.e. we select from the training data those instances that show better discrimination with respect  ... 
doi:10.1109/icpr.2010.1128 dblp:conf/icpr/LopesGKO10 fatcat:zzoqv6qe2rc5tg3swkiy7hml4y

Towards genre classification for IR in the workplace

Luanne Freund, Charles L. A. Clarke, Elaine G. Toms
2006 Proceedings of the 1st international conference on Information interaction in context - IIiX  
Use of document genre in information retrieval systems has the potential to improve the task-appropriateness of results. However, genre classification remains a challenging problem.  ...  We describe a case study of genre classification in a software engineering workplace domain, which includes the development of a genre taxonomy and experiments in automatic genre classification using supervised  ...  Thanks to Julie Waterhouse and Peter Yeung for all their valuable help with this project.  ... 
doi:10.1145/1164820.1164829 dblp:conf/iiix/FreundCT06 fatcat:753qspzmorahdfezpkwo3t7olu

UNICAMP-UFMG at MediaEval 2012: Genre Tagging Task

Jurandy Almeida, Thiago Salles, Eder Ferreira Martins, Otávio Augusto Bizetto Penatti, Ricardo da Silva Torres, Marcos André Gonçalves, Jussara M. Almeida
2012 MediaEval Benchmarking Initiative for Multimedia Evaluation  
Developed in the context of Genre Tagging Task at Media-Eval 2012, this work consists in automatically assigning genre tags to a set of Internet videos.  ...  We approach this task from the classification point of view and focus on different learning strategies: video similarity for processing visual content and an ensemble of classifiers for text-processing  ...  In order to classify a set of unseen examples, the level-0 classifiers are trained using the entire training set. The original test set is then classified, and a set of scores is generated.  ... 
dblp:conf/mediaeval/AlmeidaSMPTGA12 fatcat:msfmscx245gazfhynvm2ipq74y

A combination of local approaches for hierarchical music genre classification

Antonio R. Parmezan, Diego Furtado Silva, Gustavo Batista
2020 Zenodo  
As shown, compared to state-of-the-art approaches, our approach has a lower computational cost and can achieve competitive performances.  ...  Automatically classifying music genres is a challenging endeavor due to the inherent ambiguity and subjectivity.  ...  A classifier makes use of such characteristics to identify the music genre of the analyzed signal.  ... 
doi:10.5281/zenodo.4245540 fatcat:4j5biyo3pbdozbx4x3oedy4554

Two Attempts to Predict Author Gender in Cross-Genre Settings in Dutch

Eduardo Brito, Rafet Sifa, Christian Bauckhage
2019 Computational Linguistics in the Netherlands  
We show two alternative classification approaches: a rather standard one consisting of feature engineering and a random forest classifier; and an alternative one involving a LSTM classifier.  ...  Both are enhanced by a LDA model trained on stems. We considered various features such as frequency of function words, parts-of-speech and sentiment among others.  ...  For each of these genres, we were asked to predict the gender of the respective author by means of two different models: one trained with the text collection of the same genre (in-genre setting) and one  ... 
dblp:conf/clin/BritoSB19 fatcat:ulabnajn7bgotp2huiepyt6yqa

Exploring the Effects of Cross-Genre Machine Learning for Author Profiling in PAN 2016

Pashutan Modaresi, Matthias Liebeck, Stefan Conrad
2016 Conference and Labs of the Evaluation Forum  
We address gender and age prediction as a classification task and approach this problem by extracting stylistic and lexical features for training a logistic regression model.  ...  Furthermore, we report the effects of our cross-genre machine learning approach for the author profiling task.  ...  Acknowledgments This work was partially funded by the PhD program Online Participation, supported by the North Rhine-Westphalian funding scheme Fortschrittskollegs and by the German Federal Ministry of  ... 
dblp:conf/clef/ModaresiL016 fatcat:f3766tybazbcxfhq4tu5zb2iqy

A New Pairwise Ensemble Approach for Text Classification [chapter]

Yan Liu, Jaime Carbonell, Rong Jin
2003 Lecture Notes in Computer Science  
This new approach better captures the characteristics of genre classification, including its heterogeneous nature.  ...  In this paper we present a new pairwise ensemble approach, which uses pairwise Support Vector Machine (SVM) classifiers as base classifiers and "input-dependent latent variable" method for model combination  ...  Any opinions or findings in this material are those of the authors and do not necessarily reflect those of the sponsor.  ... 
doi:10.1007/978-3-540-39857-8_26 fatcat:sfazrf5jvbbtzblin2ld3hds24

From Multi-Labeling To Multi-Domain-Labeling: A Novel Two-Dimensional Approach To Music Genre Classification

Hanna M. Lukashevich, Jakob Abeßer, Christian Dittmar, Holger Großmann
2009 Zenodo  
THREE EVALUATION EXPERIMENTS To evaluate the improvement of the classifier performance, we perform three different experiments as depicted in Fig. 2 (a) -2(c).  ...  In addition, the approach facilitates a more precise training of a classifier by avoiding fuzzy multi-labeled data samples.  ... 
doi:10.5281/zenodo.1417534 fatcat:wbaoo5v7vvfhhlauf2woiyz5wq

Evaluating music emotion recognition: Lessons from music genre recognition?

Bob L. Sturm
2013 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)  
A fundamental problem with nearly all work in music genre recognition (MGR) is that evaluation lacks validity with respect to the principal goals of MGR.  ...  Standard approaches to evaluation, though easy to implement, do not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization  ...  This requires a different approach to evaluation; and, for the principal goals of MGR/MER, there are alternatives. Hu et al.  ... 
doi:10.1109/icmew.2013.6618342 dblp:conf/icmcs/Sturm13b fatcat:3sxyzwrp4zbvjgcjr5uk53xi7m

Multimodal KDK Classifier For Automatic Classification of Movie Trailers

2019 International journal of recent technology and engineering  
In this paper, we proposed a classifier to identify the genre of a movie trailer by analyzing it's audio and visual features simultaneously.  ...  Movie trailer classification is a field of automation of analyzing the movie trailers and classify them into one of the various genres.  ...  These genres aren't much different, but the thing is that different compositions of core genres give rise to these secondary genres.  ... 
doi:10.35940/ijrte.c4825.098319 fatcat:v4drlr27frea3gzkzyehilnjma
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