Art
J-GLOBAL ID：201502213131405972
Reference number：15A0789551
ニュース記事の時間的特性を考慮した株価動向予測
Author (3)：
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Material：
Volume：
2015
Issue：
MPS-102
Page：
VOL.2015-MPS-102,NO.4 (WEB ONLY)
Publication year：
Feb. 24, 2015
JST Material Number：
U0451A
Document type：
Proceedings
Article type：
原著論文
Country of issue：
Japan (JPN)
Language：
JAPANESE (JA)
Thesaurus term：
Thesaurus term/Semi thesaurus term
Keywords indexed to the article.
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Semi thesaurus term：
Thesaurus term/Semi thesaurus term
Keywords indexed to the article.
All keywords is available on JDreamIII(charged).
On J-GLOBAL, this item will be available after more than half a year after the record posted. In addtion, medical articles require to login to MyJ-GLOBAL.
JST classification (1)：
JST classification
Category name(code) classified by JST.
Natural language processing
Reference (22)：
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Bengio, Y., Lamblin, P., Popovici, D. and Larochelle, H.: Greedy layer-wise training of deep networks, Proceedings of the twenty-first international conference on Neural Information Processing Systems, pp. 153-160 (2007)
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Boulanger-Lewandowski, N., Bengio, Y. and Vincent, P.: Modeling temporal dependencies in high-dimensional sequences: Application to polyphonic music generation and transcription, Proceedings of the twenty-ninth International Conference on Machine Learning, pp. 1159-1166 (2012)
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Dahl, G. E., Yu, D., Deng, L. and Acero, A.: Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition, IEEE Transactions on Audio, Speech, and Language Processing, Vol. 20, No. 1, pp. 30-42 (2012)
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Ding, X., Zhang, Y., Liu, T. and Duan, J.: Using Structured Events to Predict Stock Price Movement: An Empirical Investigation, Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), Association for Computational Linguistics, pp. 1415-1425 (2014)
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Gidofalvi, G. and Elkan, C.: Using news articles to predict stock price movements, Department of Computer Science and Engineering, University of California, San Diego (2001)
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Terms in the title (4)：
Terms in the title
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