{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T19:38:23Z","timestamp":1743017903781,"version":"3.40.3"},"publisher-location":"Cham","reference-count":5,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030368012"},{"type":"electronic","value":"9783030368029"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","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":[[2019]]},"DOI":"10.1007\/978-3-030-36802-9_73","type":"book-chapter","created":{"date-parts":[[2019,12,5]],"date-time":"2019-12-05T18:03:03Z","timestamp":1575568983000},"page":"690-697","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["RL-Gen: A Character-Level Text Generation Framework with Reinforcement Learning in Domain Generation Algorithm Case"],"prefix":"10.1007","author":[{"given":"Hua","family":"Cheng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Cai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiquan","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,12,5]]},"reference":[{"key":"73_CR1","doi-asserted-by":"crossref","unstructured":"Chen, Y., Yan, S., Pang, T., Chen, R.: Detection of DGA domains based on support vector machine. In: 2018 Third International Conference on Security of Smart Cities, Industrial Control System and Communications (SSIC), Shanghai, pp. 1\u20134 (2018)","DOI":"10.1109\/SSIC.2018.8556788"},{"key":"73_CR2","doi-asserted-by":"crossref","unstructured":"Abdelwahab, O., Elmaghraby, A.: Deep learning based vs. Markov chain based text generation for cross domain adaptation for sentiment classification. In: 2018 IEEE International Conference on Information Reuse and Integration (IRI), Salt Lake City, UT, pp. 252\u2013255 (2018)","DOI":"10.1109\/IRI.2018.00046"},{"key":"73_CR3","unstructured":"Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., Courville, A.: Improved training of wasserstein GANs. arXiv preprint arXiv:1704.00028 (2017)"},{"key":"73_CR4","doi-asserted-by":"publisher","unstructured":"Chen, L., Cheng, H., Fang, Y.: Detecting domain generation algorithms based on attention mechanism. J. East Chin. Univ. Sci. Technol. (Natural Science Edition). https:\/\/doi.org\/10.14135\/j.cnki.1006-3080.20180326002","DOI":"10.14135\/j.cnki.1006-3080.20180326002"},{"key":"73_CR5","unstructured":"Arjovsky, M., Bottou, L.: Wasserstein GAN. arXiv preprint arXiv:1701.07875 (2017)"}],"container-title":["Communications in Computer and Information Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-36802-9_73","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T16:58:04Z","timestamp":1710262684000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-36802-9_73"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030368012","9783030368029"],"references-count":5,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-36802-9_73","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"5 December 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sydney, NSW","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 December 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 December 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ajiips.com.au\/iconip2019\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}