{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:51:42Z","timestamp":1740099102725,"version":"3.37.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319925363"},{"type":"electronic","value":"9783319925370"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-92537-0_39","type":"book-chapter","created":{"date-parts":[[2018,5,25]],"date-time":"2018-05-25T03:25:50Z","timestamp":1527218750000},"page":"339-345","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Recurrent Neural Network with Dynamic Memory"],"prefix":"10.1007","author":[{"given":"Jiaqi","family":"Bai","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Dong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaofeng","family":"Liao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nankun","family":"Mu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,5,26]]},"reference":[{"issue":"3","key":"39_CR1","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1109\/TASLP.2014.2383614","volume":"23","author":"Y Dauphin","year":"2015","unstructured":"Dauphin, Y., Yao, K., Bengio, Y., Deng, L., Hakkani-Tur, D., He, X., Heck, L., Tur, G., Yu, D., Zweig, G.: Using recurrent neural networks for slot filling in spoken language understanding. IEEE Trans. Audio Speech Lang. Process. 23(3), 530\u2013539 (2015)","journal-title":"IEEE Trans. Audio Speech Lang. Process."},{"issue":"7","key":"39_CR2","doi-asserted-by":"publisher","first-page":"1450","DOI":"10.1109\/TASLP.2017.2694699","volume":"25","author":"M Korpusik","year":"2017","unstructured":"Korpusik, M., Glass, J.: Spoken language understanding for a nutrition dialogue system. IEEE Trans. Audio Speech Lang. Process. 25(7), 1450\u20131461 (2017)","journal-title":"IEEE Trans. Audio Speech Lang. Process."},{"issue":"2","key":"39_CR3","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1109\/TNNLS.2015.2499302","volume":"27","author":"JT Chien","year":"2016","unstructured":"Chien, J.T., Ku, Y.C.: Bayesian recurrent neural network for language modeling. IEEE Trans. Neural Netw. Learn. Syst. 27(2), 361 (2016)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"6","key":"39_CR4","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/j.neunet.2012.11.013","volume":"41","author":"P Arena","year":"2013","unstructured":"Arena, P., Patane, L., Stornanti, V., Termini, P.S., Zapf, B., Strauss, R.: Modeling the insect mushroom bodies: application to a delayed match-to-sample task. Neural Netw. 41(6), 202\u2013211 (2013)","journal-title":"Neural Netw."},{"issue":"5","key":"39_CR5","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1109\/MIS.2015.69","volume":"30","author":"J Zhang","year":"2015","unstructured":"Zhang, J., Zong, C.: Deep neural networks in machine translation: an overview. IEEE Intell. Syst. 30(5), 16\u201325 (2015)","journal-title":"IEEE Intell. Syst."},{"issue":"12","key":"39_CR6","doi-asserted-by":"publisher","first-page":"2825","DOI":"10.1109\/TCYB.2015.2490165","volume":"46","author":"Y Chherawala","year":"2016","unstructured":"Chherawala, Y., Roy, P.P., Cheriet, M.: Feature set evaluation for offline handwriting recognition systems: application to the recurrent neural network model. IEEE Trans. Cybern. 46(12), 2825\u20132836 (2016)","journal-title":"IEEE Trans. Cybern."},{"issue":"99","key":"39_CR7","first-page":"1","volume":"PP","author":"J Wang","year":"2017","unstructured":"Wang, J., Zhang, L., Guo, Q., Yi, Z.: Recurrent neural networks with auxiliary memory units. IEEE Trans. Neural Netw. Learn. Syst. PP(99), 1\u201310 (2017)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"39_CR8","unstructured":"Gustavsson, A., Magnuson, A., Blomberg, B., Andersson, M., Halfvarson, J., Tysk, C.: On the difficulty of training recurrent neural networks. In: International Conference on Machine Learning, p. III\u20131310 (2013)"},{"key":"39_CR9","unstructured":"Weston, J., Chopra, S., Bordes, A.: Memory networks. Eprint Arxiv (2014)"},{"issue":"2","key":"39_CR10","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1037\/0033-295X.113.2.201","volume":"113","author":"MM Botvinick","year":"2006","unstructured":"Botvinick, M.M., Plaut, D.C.: Short-term memory for serial order: a recurrent neural network model. Psyc. Rev. 113(2), 201\u2013233 (2006)","journal-title":"Psyc. Rev."},{"key":"39_CR11","unstructured":"Chung, J., Gulcehre, C., Cho, K., Bengio, Y.: Gated feedback recurrent neural networks. In: Computer Science, pp. 2067\u20132075 (2015)"},{"key":"39_CR12","unstructured":"Chung, J., Gulcehre, C., Cho, K.H., Bengio, Y.: Empirical evaluation of gated recurrent neural networks on sequence modeling. Eprint Arxiv (2014)"},{"issue":"8","key":"39_CR13","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"issue":"10","key":"39_CR14","doi-asserted-by":"publisher","first-page":"2451","DOI":"10.1162\/089976600300015015","volume":"12","author":"FA Gers","year":"2000","unstructured":"Gers, F.A., Schmidhuber, J., Cummins, F.: Learning to forget: continual prediction with lstm. Neural Comput. 12(10), 2451\u20132471 (2000)","journal-title":"Neural Comput."},{"key":"39_CR15","doi-asserted-by":"crossref","unstructured":"Cho, K., Van Merrienboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., Bengio, Y.: Learning phrase representations using RNN encoder-decoder for statistical machine translation. In: Computer Science (2014)","DOI":"10.3115\/v1\/D14-1179"},{"key":"39_CR16","unstructured":"Graves, A., Wayne, G., Danihelka, I.: Neural turing machines. In: Computer Science (2014)"},{"issue":"7626","key":"39_CR17","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1038\/nature20101","volume":"538","author":"A Graves","year":"2016","unstructured":"Graves, A., Wayne, G., Reynolds, M., Harley, T., Danihelka, I., Grabskabarwiska, A., Colmenarejo, S.G., Grefenstette, E., Ramalho, T., Agapiou, J.: Hybrid computing using a neural network with dynamic external memory. Nature 538(7626), 471 (2016)","journal-title":"Nature"}],"container-title":["Lecture Notes in Computer Science","Advances in Neural Networks \u2013 ISNN 2018"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-92537-0_39","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,5,25]],"date-time":"2018-05-25T03:35:19Z","timestamp":1527219319000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-92537-0_39"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319925363","9783319925370"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-92537-0_39","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]}}}