{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T11:09:55Z","timestamp":1750158595674},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030322359"},{"type":"electronic","value":"9783030322366"}],"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\/978-3-030-32236-6_48","type":"book-chapter","created":{"date-parts":[[2019,9,29]],"date-time":"2019-09-29T19:23:57Z","timestamp":1569785037000},"page":"529-539","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["GANCoder: An Automatic Natural Language-to-Programming Language Translation Approach Based on GAN"],"prefix":"10.1007","author":[{"given":"Yabing","family":"Zhu","sequence":"first","affiliation":[]},{"given":"Yanfeng","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Huili","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Fangjing","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,9,30]]},"reference":[{"key":"48_CR1","unstructured":"Kamath, A., Das, R.: A survey on semantic parsing. CoRR abs\/1812.00978 (2018)"},{"key":"48_CR2","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., et al.: Generative adversarial nets. In: Proceedings of the 28th Advances in Neural Information Processing Systems (NIPS 2014), pp. 2672\u20132680 (2014)"},{"key":"48_CR3","doi-asserted-by":"crossref","unstructured":"Dong, L., Lapata, M.: Language to logical form with neural attention. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, Berlin, Germany, pp. 33\u201343 (2016)","DOI":"10.18653\/v1\/P16-1004"},{"key":"48_CR4","doi-asserted-by":"crossref","unstructured":"Woods, W.A.: Progress in natural language understanding: an application to lunar geology. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics of the June 4\u20138, 1973: National Computer Conference and Exposition, pp. 441\u2013450. ACM (1973)","DOI":"10.1145\/1499586.1499695"},{"key":"48_CR5","doi-asserted-by":"crossref","unstructured":"Quirk, C., Mooney, R.J., Galley, M.: Language to code: learning semantic parsers for if-this-then-that recipes. In: ACL (1), pp. 878\u2013888 (2015)","DOI":"10.3115\/v1\/P15-1085"},{"key":"48_CR6","unstructured":"Lin, X.V., Wang, C., Zettlemoyer, L., et al.: NL2Bash: a corpus and semantic parser for natural language interface to the linux operating system. In: LREC 2018 (2018)"},{"key":"48_CR7","doi-asserted-by":"crossref","unstructured":"Tai, K.S., Socher, R., Manning, C.D.: Improved semantic representations from tree-structured long short-term memory networks. In: ACL (1), pp. 1556\u20131566 (2015)","DOI":"10.3115\/v1\/P15-1150"},{"key":"48_CR8","doi-asserted-by":"crossref","unstructured":"Mou, L., Li, G., Zhang, L., et al.: Convolutional neural networks over tree structures for programming language processing. In: AAAI 2016, pp. 1287\u20131293 (2016)","DOI":"10.1609\/aaai.v30i1.10139"},{"key":"48_CR9","unstructured":"Zhang, J., Cui, L., Gouza, F.B.: EgoCoder: intelligent program synthesis with hierarchical sequential neural network model. CoRR abs\/1805.08747 (2018)"},{"key":"48_CR10","doi-asserted-by":"crossref","unstructured":"Yin, P., Neubig, G.: A syntactic neural model for general-purpose code generation. In: ACL (1), pp. 440\u2013450 (2017)","DOI":"10.18653\/v1\/P17-1041"},{"key":"48_CR11","unstructured":"Vinyals, O., Fortunato, M., Jaitly, N.: Pointer networks. In: NIPS 2015, pp. 2692\u20132700 (2015)"},{"key":"48_CR12","doi-asserted-by":"crossref","unstructured":"Yu, L., Zhang, W., Wang, J., et al.: SeqGAN: sequence generative adversarial nets with policy gradient. In: AAAI 2017, pp. 2852\u20132858 (2017)","DOI":"10.1609\/aaai.v31i1.10804"},{"key":"48_CR13","doi-asserted-by":"crossref","unstructured":"Liu, X., Kong, X., Liu, L., et al.: TreeGAN: syntax-aware sequence generation with generative adversarial networks. In: ICDM 2018, pp. 1140\u20131145 (2018)","DOI":"10.1109\/ICDM.2018.00149"},{"key":"48_CR14","series-title":"Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1007\/978-3-319-72823-0_6","volume-title":"5G for Future Wireless Networks","author":"L Chen","year":"2018","unstructured":"Chen, L., Zeng, G., Zhang, Q., Chen, X.: Tree-LSTM Guided attention pooling of DCNN for semantic sentence modeling. In: Long, K., Leung, V.C.M., Zhang, H., Feng, Z., Li, Y., Zhang, Z. (eds.) 5GWN 2017. LNICST, vol. 211, pp. 52\u201359. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-72823-0_6"},{"key":"48_CR15","doi-asserted-by":"crossref","unstructured":"Rabinovich, M., Stern, M., Klein, D.: Abstract syntax networks for code generation and semantic parsing. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, Vancouver, Canada, pp. 1139\u20131149 (2017)","DOI":"10.18653\/v1\/P17-1105"},{"key":"48_CR16","doi-asserted-by":"crossref","unstructured":"Ling, W., Blunsom, P., Grefenstette, E., et al.: Latent predictor networks for code generation. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, Berlin, Germany, pp. 599\u2013609 (2016)","DOI":"10.18653\/v1\/P16-1057"},{"key":"48_CR17","doi-asserted-by":"crossref","unstructured":"Wong, Y.W., Mooney, R.J.: Learning for semantic parsing with statistical machine translation. In: HLT-NAACL 2006 (2006)","DOI":"10.3115\/1220835.1220891"},{"key":"48_CR18","doi-asserted-by":"crossref","unstructured":"Kate, R.J., Mooney, R.J.: Using string-kernels for learning semantic parsers. In: ACL 2006 (2006)","DOI":"10.3115\/1220175.1220290"},{"key":"48_CR19","unstructured":"Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. ICLR (Poster) (2016)"},{"key":"48_CR20","unstructured":"Arjovsky, M., Chintala, S., Bottou, L.: Wasserstein generative adversarial networks. In: ICML 2017, pp. 214\u2013223 (2017)"},{"key":"48_CR21","unstructured":"Larsen, A.B.L., Snderby, S.K., Larochelle, H., Winther, O.: Autoencoding beyond pixels using a learned similarity metric. In: ICML 2016, pp. 1558\u20131566 (2016)"},{"key":"48_CR22","doi-asserted-by":"crossref","unstructured":"Woods, W.A.: Progress in natural language understanding: an application to lunar geology. In: Proceedings of the June 4\u20138, 1973, National Computer Conference and Exposition, pp. 441\u2013450. ACM (1973)","DOI":"10.1145\/1499586.1499695"},{"issue":"1","key":"48_CR23","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1023\/A:1008270110193","volume":"9","author":"X Pennec","year":"1998","unstructured":"Pennec, X., Ayache, N.: Uniform distribution, distance and expectation problems for geometric features processing. J. Math. Imaging Vis. 9(1), 49\u201367 (1998)","journal-title":"J. Math. Imaging Vis."}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Chinese Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-32236-6_48","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T05:08:23Z","timestamp":1664514503000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-32236-6_48"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030322359","9783030322366"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-32236-6_48","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"30 September 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLPCC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"CCF International Conference on Natural Language Processing and Chinese Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Dunhuang","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"9 October 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 October 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nlpcc2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/tcci.ccf.org.cn\/conference\/2019\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"softconf","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"492","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"85","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"56","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"17% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}