Mining emotional features of movies

Yang Liu; Zhonglei Gu; Yu Zhang; Yan Liu

Mining emotional features of movies

Yang Liu, Zhonglei Gu, Yu Zhang, Yan Liu

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

5 Citations (Scopus)

Abstract

In this paper, we present the algorithm designed for mining emotional features of movies. The algorithm dubbed Arousal-Valence Discriminant Preserving Embedding (AV-DPE) is proposed to extract the intrinsic features embedded in movies that are essentially differentiating in both arousal and valence directions. After dimensionality reduction, we use the neural network and support vector regressor to make the final prediction. Experimental results show that the extracted features can capture most of the discriminant information in movie emotions.

Original language	English
Title of host publication	Working Notes Proceedings of the MediaEval 2016 Workshop
Editors	Guillaume Gravier, Claire-Hélène Demarty, Hervé Bredin, Bogdan Ionescu, Christina Boididou, Emmanuel Dellandrea, Jaeyong Choi, Michael Riegler , Richard Sutcliffe, Igor Szoke, Gareth J. F. Jones, Martha Larson
Publisher	CEUR-WS
Number of pages	3
Publication status	Published - 22 Nov 2016
Event	2016 Multimedia Benchmark Workshop, MediaEval 2016 - Hilversum, Netherlands Duration: 20 Oct 2016 → 21 Oct 2016 https://ceur-ws.org/Vol-1739/

Publication series

Name	CEUR Workshop Proceedings
Publisher	CEUR-WS
Volume	1739
ISSN (Print)	1613-0073

Conference

Conference	2016 Multimedia Benchmark Workshop, MediaEval 2016
Country/Territory	Netherlands
City	Hilversum
Period	20/10/16 → 21/10/16
Internet address	https://ceur-ws.org/Vol-1739/

Scopus Subject Areas

General Computer Science

Access to Document

http://ceur-ws.org/Vol-1739/MediaEval_2016_paper_38.pdf

Cite this

Liu, Y., Gu, Z., Zhang, Y., & Liu, Y. (2016). Mining emotional features of movies. In G. Gravier, C.-H. Demarty, H. Bredin, B. Ionescu, C. Boididou, E. Dellandrea, J. Choi, M. Riegler , R. Sutcliffe, I. Szoke, G. J. F. Jones, & M. Larson (Eds.), Working Notes Proceedings of the MediaEval 2016 Workshop (CEUR Workshop Proceedings; Vol. 1739). CEUR-WS. http://ceur-ws.org/Vol-1739/MediaEval_2016_paper_38.pdf

Liu, Yang ; Gu, Zhonglei ; Zhang, Yu et al. / Mining emotional features of movies. Working Notes Proceedings of the MediaEval 2016 Workshop. editor / Guillaume Gravier ; Claire-Hélène Demarty ; Hervé Bredin ; Bogdan Ionescu ; Christina Boididou ; Emmanuel Dellandrea ; Jaeyong Choi ; Michael Riegler ; Richard Sutcliffe ; Igor Szoke ; Gareth J. F. Jones ; Martha Larson. CEUR-WS, 2016. (CEUR Workshop Proceedings).

@inproceedings{277f0da79a0e4c668aba403d2982ae6f,

title = "Mining emotional features of movies",

abstract = "In this paper, we present the algorithm designed for mining emotional features of movies. The algorithm dubbed Arousal-Valence Discriminant Preserving Embedding (AV-DPE) is proposed to extract the intrinsic features embedded in movies that are essentially differentiating in both arousal and valence directions. After dimensionality reduction, we use the neural network and support vector regressor to make the final prediction. Experimental results show that the extracted features can capture most of the discriminant information in movie emotions.",

author = "Yang Liu and Zhonglei Gu and Yu Zhang and Yan Liu",

note = "Funding Information: The authors would like to thank the reviewer for the helpful comments. This work was supported in part by the National Natural Science Foundation of China under Grant 61503317.; 2016 Multimedia Benchmark Workshop, MediaEval 2016 ; Conference date: 20-10-2016 Through 21-10-2016",

year = "2016",

month = nov,

day = "22",

language = "English",

series = "CEUR Workshop Proceedings",

publisher = "CEUR-WS",

editor = "Guillaume Gravier and Claire-H{\'e}l{\`e}ne Demarty and Herv{\'e} Bredin and Bogdan Ionescu and Christina Boididou and Emmanuel Dellandrea and Jaeyong Choi and {Riegler }, Michael and Richard Sutcliffe and Igor Szoke and Jones, {Gareth J. F.} and Martha Larson",

booktitle = "Working Notes Proceedings of the MediaEval 2016 Workshop",

url = "https://ceur-ws.org/Vol-1739/",

}

Liu, Y, Gu, Z, Zhang, Y & Liu, Y 2016, Mining emotional features of movies. in G Gravier, C-H Demarty, H Bredin, B Ionescu, C Boididou, E Dellandrea, J Choi, M Riegler , R Sutcliffe, I Szoke, GJF Jones & M Larson (eds), Working Notes Proceedings of the MediaEval 2016 Workshop. CEUR Workshop Proceedings, vol. 1739, CEUR-WS, 2016 Multimedia Benchmark Workshop, MediaEval 2016, Hilversum, Netherlands, 20/10/16. <http://ceur-ws.org/Vol-1739/MediaEval_2016_paper_38.pdf>

Mining emotional features of movies. / Liu, Yang; Gu, Zhonglei; Zhang, Yu et al.
Working Notes Proceedings of the MediaEval 2016 Workshop. ed. / Guillaume Gravier; Claire-Hélène Demarty; Hervé Bredin; Bogdan Ionescu; Christina Boididou; Emmanuel Dellandrea; Jaeyong Choi; Michael Riegler ; Richard Sutcliffe; Igor Szoke; Gareth J. F. Jones; Martha Larson. CEUR-WS, 2016. (CEUR Workshop Proceedings; Vol. 1739).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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T1 - Mining emotional features of movies

AU - Liu, Yang

AU - Gu, Zhonglei

AU - Zhang, Yu

AU - Liu, Yan

N1 - Funding Information: The authors would like to thank the reviewer for the helpful comments. This work was supported in part by the National Natural Science Foundation of China under Grant 61503317.

PY - 2016/11/22

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N2 - In this paper, we present the algorithm designed for mining emotional features of movies. The algorithm dubbed Arousal-Valence Discriminant Preserving Embedding (AV-DPE) is proposed to extract the intrinsic features embedded in movies that are essentially differentiating in both arousal and valence directions. After dimensionality reduction, we use the neural network and support vector regressor to make the final prediction. Experimental results show that the extracted features can capture most of the discriminant information in movie emotions.

AB - In this paper, we present the algorithm designed for mining emotional features of movies. The algorithm dubbed Arousal-Valence Discriminant Preserving Embedding (AV-DPE) is proposed to extract the intrinsic features embedded in movies that are essentially differentiating in both arousal and valence directions. After dimensionality reduction, we use the neural network and support vector regressor to make the final prediction. Experimental results show that the extracted features can capture most of the discriminant information in movie emotions.

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M3 - Conference proceeding

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BT - Working Notes Proceedings of the MediaEval 2016 Workshop

A2 - Gravier, Guillaume

A2 - Demarty, Claire-Hélène

A2 - Bredin, Hervé

A2 - Ionescu, Bogdan

A2 - Boididou, Christina

A2 - Dellandrea, Emmanuel

A2 - Choi, Jaeyong

A2 - Riegler , Michael

A2 - Sutcliffe, Richard

A2 - Szoke, Igor

A2 - Jones, Gareth J. F.

A2 - Larson, Martha

PB - CEUR-WS

T2 - 2016 Multimedia Benchmark Workshop, MediaEval 2016

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Mining emotional features of movies

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