{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T22:06:54Z","timestamp":1757542014213},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319700953"},{"type":"electronic","value":"9783319700960"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-70096-0_90","type":"book-chapter","created":{"date-parts":[[2017,10,25]],"date-time":"2017-10-25T01:33:18Z","timestamp":1508895198000},"page":"882-892","source":"Crossref","is-referenced-by-count":10,"title":["Stacked Denoising Autoencoder Based Stock Market Trend Prediction via K-Nearest Neighbour Data Selection"],"prefix":"10.1007","author":[{"given":"Haonan","family":"Sun","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenge","family":"Rong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiayi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiubin","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhang","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,10,26]]},"reference":[{"issue":"3","key":"90_CR1","doi-asserted-by":"crossref","first-page":"1325","DOI":"10.1016\/j.eswa.2014.09.026","volume":"42","author":"S Barak","year":"2015","unstructured":"Barak, S., Modarres, M.: Developing an approach to evaluate stocks by forecasting effective features with data mining methods. Expert Syst. Appl. 42(3), 1325\u20131339 (2015)","journal-title":"Expert Syst. Appl."},{"key":"90_CR2","unstructured":"Kamran, R.: Prediction of stock market performance by using machine learning techniques. In: Proceedings of 2017 International Conference on Innovations in Electrical Engineering and Computational Technologies (2017)"},{"issue":"2","key":"90_CR3","first-page":"189","volume":"46","author":"G Sheelapriya","year":"2017","unstructured":"Sheelapriya, G., Murugesan, R.: Stock price trend prediction using Bayesian regularised radial basis function network model. Span. J. Finan. Account. 46(2), 189\u2013211 (2017)","journal-title":"Span. J. Finan. Account."},{"key":"90_CR4","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.eswa.2017.02.041","volume":"79","author":"B Weng","year":"2017","unstructured":"Weng, B., Ahmed, M.A., Megahed, F.M.: Stock market one-day ahead movement prediction using disparate data sources. Expert Syst. Appl. 79, 153\u2013163 (2017)","journal-title":"Expert Syst. Appl."},{"key":"90_CR5","unstructured":"Ding, X., Zhang, Y., Liu, T., Duan, J.: Deep learning for event-driven stock prediction. In: Proceedings of 24th International Joint Conference on Artificial Intelligence, pp. 2327\u20132333 (2015)"},{"key":"90_CR6","doi-asserted-by":"crossref","unstructured":"Liu, Y., Qin, Z., Li, P., Wan, T.: Stock volatility prediction using recurrent neural networks with sentiment analysis. In: Proceedings of 30th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, pp. 192\u2013201 (2017)","DOI":"10.1007\/978-3-319-60042-0_22"},{"issue":"2","key":"90_CR7","doi-asserted-by":"crossref","first-page":"383","DOI":"10.2307\/2325486","volume":"25","author":"EF Fama","year":"1970","unstructured":"Fama, E.F.: Efficient capital markets: a review of theory and empirical work. J. Finan. 25(2), 383\u2013417 (1970)","journal-title":"J. Finan."},{"issue":"4","key":"90_CR8","doi-asserted-by":"crossref","first-page":"2162","DOI":"10.1016\/j.eswa.2014.10.031","volume":"42","author":"J Patel","year":"2015","unstructured":"Patel, J., Shah, S., Thakkar, P., Kotecha, K.: Predicting stock market index using fusion of machine learning techniques. Expert Syst. Appl. 42(4), 2162\u20132172 (2015)","journal-title":"Expert Syst. Appl."},{"issue":"5","key":"90_CR9","doi-asserted-by":"crossref","first-page":"e0155133","DOI":"10.1371\/journal.pone.0155133","volume":"11","author":"M Qiu","year":"2016","unstructured":"Qiu, M., Yu, S.: Predicting the direction of stock market index movement using an optimized artificial neural network model. Plos One 11(5), e0155133 (2016)","journal-title":"Plos One"},{"issue":"5","key":"90_CR10","doi-asserted-by":"crossref","first-page":"5311","DOI":"10.1016\/j.eswa.2010.10.027","volume":"38","author":"Y Kara","year":"2011","unstructured":"Kara, Y., Boyacioglu, M.A., Baykan, \u00d6.K.: Predicting direction of stock price index movement using artificial neural networks and support vector machines: the sample of the Istanbul stock exchange. Expert Syst. Appl. 38(5), 5311\u20135319 (2011)","journal-title":"Expert Syst. Appl."},{"issue":"1","key":"90_CR11","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/j.eswa.2014.07.040","volume":"42","author":"J Patel","year":"2015","unstructured":"Patel, J., Shah, S., Thakkar, P., Kotecha, K.: Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques. Expert Syst. Appl. 42(1), 259\u2013268 (2015)","journal-title":"Expert Syst. Appl."},{"key":"90_CR12","doi-asserted-by":"crossref","unstructured":"Lin, Y., Guo, H., Hu, J.: An svm-based approach for stock market trend prediction. In: Proceedings of 2013 International Joint Conference on Neural Networks, pp. 1\u20137 (2013)","DOI":"10.1109\/IJCNN.2013.6706743"},{"key":"90_CR13","unstructured":"Weerachart, L., Nunnapus, B.: Stock price trend prediction using artificial neural network techniques: case study: Thailand stock exchange. In: Computer Science and Engineering Conference (2017)"},{"key":"90_CR14","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1016\/j.eswa.2017.02.044","volume":"80","author":"Y Chen","year":"2017","unstructured":"Chen, Y., Hao, Y.: A feature weighted support vector machine and k-nearest neighbor algorithm for stock market indices prediction. Expert Syst. Appl. 80, 340\u2013355 (2017)","journal-title":"Expert Syst. Appl."},{"issue":"20","key":"90_CR15","doi-asserted-by":"crossref","first-page":"7046","DOI":"10.1016\/j.eswa.2015.05.013","volume":"42","author":"M Ballings","year":"2015","unstructured":"Ballings, M., den Poel, D.V., Hespeels, N., Gryp, R.: Evaluating multiple classifiers for stock price direction prediction. Expert Syst. Appl. 42(20), 7046\u20137056 (2015)","journal-title":"Expert Syst. Appl."},{"key":"90_CR16","doi-asserted-by":"crossref","unstructured":"Bengio, Y., Lamblin, P., Popovici, D., Larochelle, H.: Greedy layer-wise training of deep networks. In: Proceedings of 20th Annual Conference on Neural Information Processing Systems, pp. 153\u2013160 (2006)","DOI":"10.7551\/mitpress\/7503.003.0024"},{"key":"90_CR17","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.dss.2016.03.001","volume":"85","author":"Y Shynkevich","year":"2016","unstructured":"Shynkevich, Y., McGinnity, T.M., Coleman, S.A., Belatreche, A.: Forecasting movements of health-care stock prices based on different categories of news articles using multiple kernel learning. Decis. Support Syst. 85, 74\u201383 (2016)","journal-title":"Decis. Support Syst."},{"key":"90_CR18","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.asoc.2015.06.005","volume":"35","author":"LA Laboissiere","year":"2015","unstructured":"Laboissiere, L.A., Fernandes, R.A.S., Lage, G.G.: Maximum and minimum stock price forecasting of Brazilian power distribution companies based on artificial neural networks. Appl. Soft Comput. 35, 66\u201374 (2015)","journal-title":"Appl. Soft Comput."},{"issue":"5","key":"90_CR19","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1080\/14697688.2015.1070960","volume":"16","author":"M Gorenc Novak","year":"2016","unstructured":"Gorenc Novak, M., Velu\u0161\u010dek, D.: Prediction of stock price movement based on daily high prices. Quant. Finan. 16(5), 793\u2013826 (2016)","journal-title":"Quant. Finan."},{"key":"90_CR20","unstructured":"Milosevic, N.: Equity forecast: Predicting long term stock price movement using machine learning (2016). arXiv preprint: arXiv:1603.00751"},{"issue":"3","key":"90_CR21","doi-asserted-by":"crossref","first-page":"2177","DOI":"10.1016\/j.eswa.2010.08.004","volume":"38","author":"C Yeh","year":"2011","unstructured":"Yeh, C., Huang, C., Lee, S.: A multiple-kernel support vector regression approach for stock market price forecasting. Expert Syst. Appl. 38(3), 2177\u20132186 (2011)","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"90_CR22","doi-asserted-by":"crossref","first-page":"1102","DOI":"10.1109\/TSMCB.2012.2223815","volume":"43","author":"S Chen","year":"2013","unstructured":"Chen, S., Manalu, G.M.T., Pan, J., Liu, H.: Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization techniques. IEEE Trans. Cybern. 43(3), 1102\u20131117 (2013)","journal-title":"IEEE Trans. Cybern."},{"issue":"6","key":"90_CR23","first-page":"106","volume":"4","author":"BI Sadegh","year":"2014","unstructured":"Sadegh, B.I., Mohammad, B.: Forecasting the direction of stock market index movement using three data mining techniques: the case of tehran stock exchange. Int. J. Eng. Res. Appl. 4(6), 106\u2013117 (2014)","journal-title":"Int. J. Eng. Res. Appl."},{"key":"90_CR24","doi-asserted-by":"crossref","unstructured":"Dixon, M.F., Klabjan, D., Bang, J.H.: Classification-based financial markets prediction using deep neural networks. In: Algorithmic Finance, pp. 1\u201320 (2016)","DOI":"10.2139\/ssrn.2756331"},{"key":"90_CR25","doi-asserted-by":"crossref","unstructured":"Akita, R., Yoshihara, A., Matsubara, T., Uehara, K.: Deep learning for stock prediction using numerical and textual information. In: Proceedings of 15th IEEE\/ACIS International Conference on Computer and Information Science, pp. 1\u20136 (2016)","DOI":"10.1109\/ICIS.2016.7550882"},{"issue":"22","key":"90_CR26","doi-asserted-by":"crossref","first-page":"1857","DOI":"10.1049\/el.2016.2626","volume":"52","author":"Z Zeng","year":"2016","unstructured":"Zeng, Z., Xiao, H., Zhang, X.: Self CNN-based time series stream forecasting. Electron. Lett. 52(22), 1857\u20131858 (2016)","journal-title":"Electron. Lett."},{"issue":"6","key":"90_CR27","doi-asserted-by":"crossref","first-page":"3234","DOI":"10.1016\/j.eswa.2014.12.003","volume":"42","author":"AM Rather","year":"2015","unstructured":"Rather, A.M., Agarwal, A., Sastry, V.N.: Recurrent neural network and a hybrid model for prediction of stock returns. Expert Syst. Appl. 42(6), 3234\u20133241 (2015)","journal-title":"Expert Syst. Appl."},{"key":"90_CR28","first-page":"3371","volume":"11","author":"P Vincent","year":"2010","unstructured":"Vincent, P., Larochelle, H., Lajoie, I., Bengio, Y., Manzagol, P.: Stacked denoising autoencoders: learning useful representations in a deep network with a local denoising criterion. J. Mach. Learn. Res. 11, 3371\u20133408 (2010)","journal-title":"J. Mach. Learn. Res."}],"container-title":["Lecture Notes in Computer Science","Neural Information Processing"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-70096-0_90","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,27]],"date-time":"2023-08-27T14:28:40Z","timestamp":1693146520000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-70096-0_90"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319700953","9783319700960"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-70096-0_90","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]}}}