{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:28:39Z","timestamp":1740122919922,"version":"3.37.3"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"20","license":[{"start":{"date-parts":[[2020,10,21]],"date-time":"2020-10-21T00:00:00Z","timestamp":1603238400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,10,21]],"date-time":"2020-10-21T00:00:00Z","timestamp":1603238400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,8]]},"DOI":"10.1007\/s11042-020-09967-3","type":"journal-article","created":{"date-parts":[[2020,10,21]],"date-time":"2020-10-21T09:03:01Z","timestamp":1603270981000},"page":"30827-30838","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Improving AMR parsing by exploiting the dependency parsing as an auxiliary task"],"prefix":"10.1007","volume":"80","author":[{"given":"Taizhong","family":"Wu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1919-8227","authenticated-orcid":false,"given":"Junsheng","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Weiguang","family":"Qu","sequence":"additional","affiliation":[]},{"given":"Yanhui","family":"Gu","sequence":"additional","affiliation":[]},{"given":"Bin","family":"Li","sequence":"additional","affiliation":[]},{"given":"Huilin","family":"Zhong","sequence":"additional","affiliation":[]},{"given":"Yunfei","family":"Long","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,21]]},"reference":[{"key":"9967_CR1","doi-asserted-by":"crossref","unstructured":"Ballesteros M, Al-Onaizan Y (2017) Amr parsing using stack-lstms. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp 1269\u20131275","DOI":"10.18653\/v1\/D17-1130"},{"key":"9967_CR2","unstructured":"Banarescu L, Bonial C, Cai S, Georgescu M, Griffitt K, Hermjakob U, Knight K, Koehn P, Palmer M, Schneider N (2013) Abstract meaning representation for sembanking. In: Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse, pp 178\u2013186"},{"key":"9967_CR3","unstructured":"Cheng X, Roth D (2013) Relational inference for wikification. In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pp 1787\u20131796"},{"key":"9967_CR4","doi-asserted-by":"crossref","unstructured":"Damonte M, Cohen SB, Satta G (2017) An incremental parser for abstract meaning representation. In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, pp 536\u2013546","DOI":"10.18653\/v1\/E17-1051"},{"key":"9967_CR5","unstructured":"Dozat T, Manning CD (2017) Deep biaffine attention for neural dependency parsing. In: Proceedings of the 5th International Conference on Learning Representations"},{"key":"9967_CR6","doi-asserted-by":"crossref","unstructured":"Dozat T, Qi P, Manning C D (2017) Stanford\u2019s graph-based neural dependency parser at the conll 2017 shared task. In: Proceedings of the CoNLL 2017 Shared Task, Multilingual Parsing from Raw Text to Universal Dependencies, pp 20\u201330","DOI":"10.18653\/v1\/K17-3002"},{"key":"9967_CR7","doi-asserted-by":"crossref","unstructured":"Flanigan J, Thomson S, Carbonell J, Dyer C, Smith N A (2014) A discriminative graph-based parser for the abstract meaning representation. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, vol 1, pp 1426\u20131436","DOI":"10.3115\/v1\/P14-1134"},{"key":"9967_CR8","doi-asserted-by":"crossref","unstructured":"Foland W, Martin JH (2017) Abstract meaning representation parsing using lstm recurrent neural networks. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pp 463\u2013472","DOI":"10.18653\/v1\/P17-1043"},{"key":"9967_CR9","doi-asserted-by":"crossref","unstructured":"Goodman J, Vlachos A, Naradowsky J (2016) Noise reduction and targeted exploration in imitation learning for abstract meaning representation parsing. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, vol 1, pp 1\u201311","DOI":"10.18653\/v1\/P16-1001"},{"key":"9967_CR10","doi-asserted-by":"crossref","unstructured":"Hershcovich D, Abend O, Rappoport A (2018) Multitask parsing across semantic representations. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pp 373\u2013385","DOI":"10.18653\/v1\/P18-1035"},{"key":"9967_CR11","doi-asserted-by":"crossref","unstructured":"Konstas I, Iyer S, Yatskar M, Choi Y, Zettlemoyer L (2017) Neural amr: Sequence-to-sequence models for parsing and generation. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pp 146\u2013157","DOI":"10.18653\/v1\/P17-1014"},{"key":"9967_CR12","doi-asserted-by":"crossref","unstructured":"Kuncoro A, Ballesteros M, Kong L, Dyer C, Neubig G, Smith NA (2017) What do recurrent neural network grammars learn about syntax? In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, pp 1249\u20131258","DOI":"10.18653\/v1\/E17-1117"},{"key":"9967_CR13","doi-asserted-by":"crossref","unstructured":"Lyu C, Titov I (2018) Amr parsing as graph prediction with latent alignment. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pp 397\u2013407","DOI":"10.18653\/v1\/P18-1037"},{"key":"9967_CR14","doi-asserted-by":"crossref","unstructured":"Peters M, Neumann M, Iyyer M, Gardner M, Clark C, Lee K, Zettlemoyer L (2018) Deep contextualized word representations. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics, pp 2227\u20132237","DOI":"10.18653\/v1\/N18-1202"},{"key":"9967_CR15","doi-asserted-by":"crossref","unstructured":"Puzikov Y, Kawahara D, Kurohashi S (2016) M2l at semeval-2016 task 8: Amr parsing with neural networks. In: Proceedings of the 10th international workshop on semantic evaluation (semeval-2016), pp 1154\u20131159","DOI":"10.18653\/v1\/S16-1178"},{"issue":"2","key":"9967_CR16","first-page":"547","volume":"59","author":"J Qiu","year":"2019","unstructured":"Qiu J, Liu Y, Chai Y, Si Y, Su S, Wang L, Wu Y (2019) Dependency-based local attention approach to neural machine translation. Comput Mater Cont 59(2):547\u2013562","journal-title":"Comput Mater Cont"},{"key":"9967_CR17","doi-asserted-by":"crossref","unstructured":"Strubell E, Verga P, Andor D, Weiss D, McCallum A (2018) Linguistically-informed self-attention for semantic role labeling. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp 5027\u20135038","DOI":"10.18653\/v1\/D18-1548"},{"key":"9967_CR18","first-page":"93","volume":"7","author":"R van Noord","year":"2017","unstructured":"van Noord R, Bos J (2017) Neural semantic parsing by character-based translation: Experiments with abstract meaning representations. Comput Linguist Netherlands J 7:93\u2013108","journal-title":"Comput Linguist Netherlands J"},{"key":"9967_CR19","doi-asserted-by":"crossref","unstructured":"Wang C, Xue N, Pradhan S (2015a) A transition-based algorithm for amr parsing. In: Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics, pp 366\u2013375","DOI":"10.3115\/v1\/N15-1040"},{"key":"9967_CR20","doi-asserted-by":"crossref","unstructured":"Wang C, Xue N, Pradhan S (2015b) Boosting transition-based amr parsing with refined actions and auxiliary analyzers. In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics, pp 857\u2013862","DOI":"10.3115\/v1\/P15-2141"},{"key":"9967_CR21","doi-asserted-by":"crossref","unstructured":"Wang C, Xue N (2017) Getting the most out of amr parsing. In: Proceedings of the 2017 conference on empirical methods in natural language processing, pp 1257\u20131268","DOI":"10.18653\/v1\/D17-1129"},{"issue":"3","key":"9967_CR22","first-page":"603","volume":"57","author":"S Wang","year":"2018","unstructured":"Wang S, Zhang L, Zhang Y, Sun J, Pang C, Tian G, Cao N (2018) Natural language semantic construction based on cloud database. Comput Mater Cont 57(3):603\u2013619","journal-title":"Comput Mater Cont"},{"key":"9967_CR23","doi-asserted-by":"crossref","unstructured":"Werling K, Angeli G, Manning C D (2015) Robust subgraph generation improves abstract meaning representation parsing. In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics, vol 1, pp 982\u2013991","DOI":"10.3115\/v1\/P15-1095"},{"key":"9967_CR24","doi-asserted-by":"crossref","unstructured":"Xu K, Wu L, Wang Z, Yu M, Chen L, Sheinin V (2018) Exploiting rich syntactic information for semantic parsing with graph-to-sequence model. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp 918\u2013924","DOI":"10.18653\/v1\/D18-1110"},{"issue":"2","key":"9967_CR25","first-page":"569","volume":"61","author":"K Yang","year":"2019","unstructured":"Yang K, Wang Y, Zhang W, Yao J, Le Y (2019) Keyphrase generation based on self-attention mechanism. Comput Mater Cont 61(2):569\u2013581","journal-title":"Comput Mater Cont"},{"key":"9967_CR26","doi-asserted-by":"crossref","unstructured":"Zhang S, Ma X, Duh K, Durme BV (2019) Amr parsing as sequence-to-graph transduction. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics","DOI":"10.18653\/v1\/P19-1009"},{"key":"9967_CR27","doi-asserted-by":"crossref","unstructured":"Zhou J, Xu F, Uszkoreit H, Weiguang Q, Li R, Gu Y (2016) Amr parsing with an incremental joint model. In: Proceedings of the 2016 conference on empirical methods in natural language processing, pp 680\u2013689","DOI":"10.18653\/v1\/D16-1065"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09967-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-020-09967-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09967-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T23:43:41Z","timestamp":1634773421000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-020-09967-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,21]]},"references-count":27,"journal-issue":{"issue":"20","published-print":{"date-parts":[[2021,8]]}},"alternative-id":["9967"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-09967-3","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2020,10,21]]},"assertion":[{"value":"26 March 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 June 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 September 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 October 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}