{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T01:28:30Z","timestamp":1743125310568,"version":"3.40.3"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030884796"},{"type":"electronic","value":"9783030884802"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-88480-2_2","type":"book-chapter","created":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T11:04:52Z","timestamp":1633950292000},"page":"15-26","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Chinese Macro Discourse Parsing on Dependency Graph Convolutional Network"],"prefix":"10.1007","author":[{"given":"Yaxin","family":"Fan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaomin","family":"Chu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peifeng","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiaoming","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,10,6]]},"reference":[{"key":"2_CR1","doi-asserted-by":"crossref","unstructured":"Carlson, L., Marcu, D., Okurowski, M.E.: Building a Discourse-Tagged Corpus in the Framework of Rhetorical Structure Theory, pp. 85\u2013112 (2003)","DOI":"10.1007\/978-94-010-0019-2_5"},{"key":"2_CR2","unstructured":"Che, W., Li, Z., Liu, T.: LTP: a chinese language technology platform. In: COLING, pp. 13\u201316 (2010)"},{"key":"2_CR3","doi-asserted-by":"crossref","unstructured":"Chen, D., Manning, C.: A fast and accurate dependency parser using neural networks. In: EMNLP, pp. 740\u2013750 (2014)","DOI":"10.3115\/v1\/D14-1082"},{"key":"2_CR4","doi-asserted-by":"crossref","unstructured":"Choubey, P.K., Lee, A., Huang, R., Wang, L.: Discourse as a function of event: profiling discourse structure in news articles around the main event. In: ACL, pp. 5374\u20135386 (2020)","DOI":"10.18653\/v1\/2020.acl-main.478"},{"key":"2_CR5","unstructured":"Fan, Y., Jiang, F., Chu, X., Li, P., Zhu, Q.: Combining global and local information to recognize Chinese macro discourse structure. In: CCL, pp. 183\u2013194 (2020)"},{"key":"2_CR6","doi-asserted-by":"crossref","unstructured":"Feng, V.W., Hirst, G.: A linear-time bottom-up discourse parser with constraints and post-editing. In: ACL, pp. 511\u2013521 (2014)","DOI":"10.3115\/v1\/P14-1048"},{"key":"2_CR7","doi-asserted-by":"crossref","unstructured":"Guo, F., He, R., Dang, J., Wang, J.: Working memory-driven neural networks with a novel knowledge enhancement paradigm for implicit discourse relation recognition. In: AAAI, pp. 7822\u20137829 (2020)","DOI":"10.1609\/aaai.v34i05.6287"},{"issue":"3","key":"2_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.5087\/dad.2010.003","volume":"1","author":"H Hernault","year":"2010","unstructured":"Hernault, H., Prendinger, H., du Verle, D.A., Ishizuka, M.: Hilda: a discourse parser using support vector machine classification. Dialogue Discourse 1(3), 1\u201333 (2010)","journal-title":"Dialogue Discourse"},{"key":"2_CR9","doi-asserted-by":"crossref","unstructured":"Ji, Y., Eisenstein, J.: Representation learning for text-level discourse parsing. In: ACL, pp. 13\u201324 (2014)","DOI":"10.3115\/v1\/P14-1002"},{"key":"2_CR10","doi-asserted-by":"crossref","unstructured":"Jiang, F., Chu, X., Li, P., Kong, F., Zhu, Q.: Chinese paragraph-level discourse parsing with global backward and local reverse reading. In: COLING, pp. 5749\u20135759 (2020)","DOI":"10.18653\/v1\/2020.coling-main.506"},{"key":"2_CR11","doi-asserted-by":"crossref","unstructured":"Jiang, F., Fan, Y., Chu, X., Li, P., Zhu, Q., Kong, F.: Hierarchical macro discourse parsing based on topic segmentation. In: AAAI (2021)","DOI":"10.1609\/aaai.v35i14.17554"},{"key":"2_CR12","doi-asserted-by":"crossref","unstructured":"Jiang, F., Li, P., Chu, X., Zhu, Q., Zhou, G.: Recognizing macro chinese discourse structure on label degeneracy combination model. In: NLPCC, pp. 92\u2013104 (2018)","DOI":"10.1007\/978-3-319-99501-4_8"},{"key":"2_CR13","unstructured":"Jiang, F., Xu, S., Chu, X., Li, P., Zhu, Q., Zhou, G.: Mcdtb: a macro-level chinese discourse treebank. In: Coling, pp. 3493\u20133504 (2018)"},{"key":"2_CR14","unstructured":"Joty, S., Carenini, G., Ng, R., Mehdad, Y.: Combining intra- and multi-sentential rhetorical parsing for document-level discourse analysis. In: ACL, pp. 486\u2013496 (2013)"},{"key":"2_CR15","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"2_CR16","doi-asserted-by":"crossref","unstructured":"Li, Z., Wu, W., Li, S.: Composing elementary discourse units in abstractive summarization. In: ACL, pp. 6191\u20136196, July 2020","DOI":"10.18653\/v1\/2020.acl-main.551"},{"key":"2_CR17","doi-asserted-by":"crossref","unstructured":"Lin, X., Joty, S., Jwalapuram, P., Bari, M.S.: A unified linear-time framework for sentence-level discourse parsing. In: ACL, pp. 4190\u20134200 (2019)","DOI":"10.18653\/v1\/P19-1410"},{"key":"2_CR18","doi-asserted-by":"crossref","unstructured":"Liu, L., Lin, X., Joty, S., Han, S., Bing, L.: Hierarchical pointer net parsing. In: EMNLP-IJCNLP, pp. 1007\u20131017 (2019)","DOI":"10.18653\/v1\/D19-1093"},{"key":"2_CR19","doi-asserted-by":"crossref","unstructured":"Ma, N., Mazumder, S., Wang, H., Liu, B.: Entity-aware dependency-based deep graph attention network for comparative preference classification. In: ACL, pp. 5782\u20135788 (2020)","DOI":"10.18653\/v1\/2020.acl-main.512"},{"key":"2_CR20","doi-asserted-by":"crossref","unstructured":"Mann, W.C., Thompson, S.A.: Rhetorical Structure Theory: A Theory of Text Organization. University of Southern California, Information Sciences Institute Los Angeles (1987)","DOI":"10.1515\/text.1.1988.8.3.243"},{"key":"2_CR21","doi-asserted-by":"crossref","unstructured":"Meng, F., Feng, J., Yin, D., Chen, S., Hu, M.: Sentiment analysis with weighted graph convolutional networks. In: EMNLP: Findings, pp. 586\u2013595 (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.52"},{"issue":"11","key":"2_CR22","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1145\/219717.219748","volume":"38","author":"GA Miller","year":"1995","unstructured":"Miller, G.A.: Wordnet: a lexical database for english. Commun. ACM 38(11), 39\u201341 (1995)","journal-title":"Commun. ACM"},{"key":"2_CR23","doi-asserted-by":"crossref","unstructured":"Sporleder, C., Lascarides, A.: Combining hierarchical clustering and machine learning to predict high-level discourse structure. In: COLING, pp. 43\u201349 (2004)","DOI":"10.3115\/1220355.1220362"},{"key":"2_CR24","doi-asserted-by":"crossref","unstructured":"Wang, Y., Li, S., Wang, H.: A two-stage parsing method for text-level discourse analysis. In: ACL, pp. 184\u2013188 (2017)","DOI":"10.18653\/v1\/P17-2029"},{"key":"2_CR25","doi-asserted-by":"crossref","unstructured":"Xu, B., et al.: Cn-dbpedia: a never-ending chinese knowledge extraction system. In: Benferhat, S., Tabia, K., Ali, M. (eds.) Advances in Artificial Intelligence: From Theory to Practice, pp. 428\u2013438 (2017)","DOI":"10.1007\/978-3-319-60045-1_44"},{"key":"2_CR26","doi-asserted-by":"crossref","unstructured":"Zhang, C., Li, Q., Song, D.: Aspect-based sentiment classification with aspect-specific graph convolutional networks. In: EMNLP-IJCNLP, pp. 4568\u20134578 (2019)","DOI":"10.18653\/v1\/D19-1464"},{"key":"2_CR27","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Chu, X., Li, P., Zhu, Q.: Constructing chinese macro discourse tree via multiple views and word pair similarity. In: Tang, J., Kan, M.Y., Zhao, D., Li, S., Zan, H. (eds.) NLPCC, pp. 773\u2013786 (2019)","DOI":"10.1007\/978-3-030-32233-5_60"}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Chinese Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-88480-2_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T20:02:40Z","timestamp":1725912160000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-88480-2_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030884796","9783030884802"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-88480-2_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"6 October 2021","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":"Qingdao","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":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nlpcc2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/tcci.ccf.org.cn\/conference\/2021\/","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":"446","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":"66","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":"0","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":"15% - 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":"1.5","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)"}},{"value":"23 poster papers and 27 workshop papers are also included.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}