{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T00:40:40Z","timestamp":1742949640070,"version":"3.40.3"},"publisher-location":"Cham","reference-count":36,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030731960"},{"type":"electronic","value":"9783030731977"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/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":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-73197-7_3","type":"book-chapter","created":{"date-parts":[[2021,4,6]],"date-time":"2021-04-06T19:03:01Z","timestamp":1617735781000},"page":"37-52","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Keyword-Aware Encoder for Abstractive Text Summarization"],"prefix":"10.1007","author":[{"given":"Tianxiang","family":"Hu","sequence":"first","affiliation":[]},{"given":"Jingxi","family":"Liang","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Ye","sequence":"additional","affiliation":[]},{"given":"Shikun","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,4,6]]},"reference":[{"key":"3_CR1","unstructured":"The stanford nlp group: Stanford dependencies. https:\/\/nlp.stanford.edu\/software\/stanford-dependencies.shtml"},{"key":"3_CR2","unstructured":"Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014)"},{"key":"3_CR3","doi-asserted-by":"crossref","unstructured":"Banko, M., Mittal, V.O., Witbrock, M.J.: Headline generation based on statistical translation. In: Proceedings of the 38th Annual Meeting on Association for Computational Linguistics, pp. 318\u2013325. Association for Computational Linguistics (2000)","DOI":"10.3115\/1075218.1075259"},{"key":"3_CR4","doi-asserted-by":"crossref","unstructured":"Cao, Z., Li, W., Li, S., Wei, F.: Retrieve, rerank and rewrite: soft template based neural summarization. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, ACL 2018, Melbourne, Australia, 15\u201320 July 2018, vol. 1: Long Papers, pp. 152\u2013161 (2018)","DOI":"10.18653\/v1\/P18-1015"},{"key":"3_CR5","unstructured":"Che, W., Li, Z., Liu, T.: Ltp: a Chinese language technology platform. In: Proceedings of the 23rd International Conference on Computational Linguistics: Demonstrations, pp. 13\u201316. Association for Computational Linguistics (2010)"},{"key":"3_CR6","unstructured":"Chen, Q., Zhu, X., Ling, Z., Wei, S., Jiang, H.: Distraction-based neural networks for document summarization. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, pp. 2754\u20132760. AAAI Press (2016)"},{"key":"3_CR7","doi-asserted-by":"crossref","unstructured":"Chen, Y.C., Bansal, M.: Fast abstractive summarization with reinforce-selected sentence rewriting. arXiv preprint arXiv:1805.11080 (2018)","DOI":"10.18653\/v1\/P18-1063"},{"key":"3_CR8","doi-asserted-by":"crossref","unstructured":"Chen, Y., Gan, Z., Cheng, Y., Liu, J., Liu, J.: Distilling knowledge learned in BERT for text generation. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 7893\u20137905. Association for Computational Linguistics (2020)","DOI":"10.18653\/v1\/2020.acl-main.705"},{"key":"3_CR9","doi-asserted-by":"crossref","unstructured":"Cohan, A., et al.: A discourse-aware attention model for abstractive summarization of long documents. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol. 2 (Short Papers), pp. 615\u2013621 (2018)","DOI":"10.18653\/v1\/N18-2097"},{"issue":"Jul","key":"3_CR10","first-page":"2121","volume":"12","author":"J Duchi","year":"2011","unstructured":"Duchi, J., Hazan, E., Singer, Y.: Adaptive subgradient methods for online learning and stochastic optimization. J. Mach. Learn. Res. 12(Jul), 2121\u20132159 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"3_CR11","doi-asserted-by":"crossref","unstructured":"Gao, S., Chen, X., Li, P., Chan, Z., Zhao, D., Yan, R.: How to write summaries with patterns? learning towards abstractive summarization through prototype editing. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, pp. 3739\u20133749 (2019)","DOI":"10.18653\/v1\/D19-1388"},{"key":"3_CR12","doi-asserted-by":"crossref","unstructured":"Gehrmann, S., Deng, Y., Rush, A.M.: Bottom-up abstractive summarization. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, 31 October\u20134 November 2018, pp. 4098\u20134109 (2018)","DOI":"10.18653\/v1\/D18-1443"},{"key":"3_CR13","unstructured":"Glorot, X., Bengio, Y.: Understanding the difficulty of training deep feedforward neural networks. In: Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, pp. 249\u2013256 (2010)"},{"key":"3_CR14","doi-asserted-by":"crossref","unstructured":"Gu, J., Lu, Z., Li, H., Li, V.O.: Incorporating copying mechanism in sequence-to-sequence learning. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, vol. 1: Long Papers), pp. 1631\u20131640 (2016)","DOI":"10.18653\/v1\/P16-1154"},{"issue":"8","key":"3_CR15","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."},{"key":"3_CR16","doi-asserted-by":"crossref","unstructured":"Hsu, W.T., Lin, C.K., Lee, M.Y., Min, K., Tang, J., Sun, M.: A unified model for extractive and abstractive summarization using inconsistency loss. arXiv preprint arXiv:1805.06266 (2018)","DOI":"10.18653\/v1\/P18-1013"},{"key":"3_CR17","doi-asserted-by":"crossref","unstructured":"Hu, B., Chen, Q., Zhu, F.: LCSTS: a large scale Chinese short text summarization dataset. arXiv preprint arXiv:1506.05865 (2015)","DOI":"10.18653\/v1\/D15-1229"},{"key":"3_CR18","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"942","DOI":"10.1007\/978-3-319-73618-1_84","volume-title":"Natural Language Processing and Chinese Computing","author":"L Hua","year":"2018","unstructured":"Hua, L., Wan, X., Li, L.: Overview of the NLPCC 2017 shared task: single document summarization. In: Huang, X., Jiang, J., Zhao, D., Feng, Y., Hong, Yu. (eds.) NLPCC 2017. LNCS (LNAI), vol. 10619, pp. 942\u2013947. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-73618-1_84"},{"issue":"1","key":"3_CR19","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1016\/S0004-3702(02)00222-9","volume":"139","author":"K Knight","year":"2002","unstructured":"Knight, K., Marcu, D.: Summarization beyond sentence extraction: a probabilistic approach to sentence compression. Artif Intell. 139(1), 91\u2013107 (2002)","journal-title":"Artif Intell.."},{"key":"3_CR20","doi-asserted-by":"crossref","unstructured":"Li, C., Xu, W., Li, S., Gao, S.: Guiding generation for abstractive text summarization based on key information guide network. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol. 2 (Short Papers), pp. 55\u201360 (2018)","DOI":"10.18653\/v1\/N18-2009"},{"key":"3_CR21","doi-asserted-by":"crossref","unstructured":"Li, P., Lam, W., Bing, L., Wang, Z.: Deep recurrent generative decoder for abstractive text summarization. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 2091\u20132100 (2017)","DOI":"10.18653\/v1\/D17-1222"},{"key":"3_CR22","unstructured":"Lin, C.Y.: Rouge: A package for automatic evaluation of summaries. Text Summarization Branches Out (2004)"},{"key":"3_CR23","doi-asserted-by":"crossref","unstructured":"Luong, T., Pham, H., Manning, C.D.: Effective approaches to attention-based neural machine translation. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 1412\u20131421 (2015)","DOI":"10.18653\/v1\/D15-1166"},{"key":"3_CR24","doi-asserted-by":"crossref","unstructured":"Pasunuru, R., Bansal, M.: Multireward reinforced summarization with saliency and entailment. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol. 2 (Short Papers), pp. 646\u2013653 (2018)","DOI":"10.18653\/v1\/N18-2102"},{"key":"3_CR25","unstructured":"Paulus, R., Xiong, C., Socher, R.: A deep reinforced model for abstractive summarization. arXiv preprint arXiv:1705.04304 (2017)"},{"key":"3_CR26","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., Manning, C.: Glove: global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"},{"key":"3_CR27","doi-asserted-by":"crossref","unstructured":"Rush, A.M., Chopra, S., Weston, J.: A neural attention model for abstractive sentence summarization. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 379\u2013389 (2015)","DOI":"10.18653\/v1\/D15-1044"},{"key":"3_CR28","doi-asserted-by":"crossref","unstructured":"See, A., Liu, P.J., Manning, C.D.: Get to the point: summarization with pointer-generator networks. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, vol. 1: Long Papers, pp. 1073\u20131083 (2017)","DOI":"10.18653\/v1\/P17-1099"},{"issue":"1","key":"3_CR29","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1), 1929\u20131958 (2014)","journal-title":"J. Mach. Learn. Res."},{"key":"3_CR30","unstructured":"Sutskever, I., Vinyals, O., Le, Q.V.: Sequence to sequence learning with neural networks. In: Advances in Neural Information Processing Systems, pp. 3104\u20133112 (2014)"},{"key":"3_CR31","doi-asserted-by":"crossref","unstructured":"Tan, J., Wan, X., Xiao, J.: Abstractive document summarization with a graph-based attentional neural model. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pp. 1171\u20131181 (2017)","DOI":"10.18653\/v1\/P17-1108"},{"key":"3_CR32","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, pp. 6000\u20136010 (2017)"},{"key":"3_CR33","doi-asserted-by":"crossref","unstructured":"Wang, K., Quan, X., Wang, R.: Biset: bi-directional selective encoding with template for abstractive summarization. In: Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, 28 July\u20132 August 2019, vol. 1: Long Papers, pp. 2153\u20132162 (2019)","DOI":"10.18653\/v1\/P19-1207"},{"key":"3_CR34","unstructured":"Xu, L., Wang, Z., Liu, Z., Sun, M., et al.: Topic sensitive neural headline generation. arXiv preprint arXiv:1608.05777 (2016)"},{"issue":"6","key":"3_CR35","doi-asserted-by":"publisher","first-page":"1549","DOI":"10.1016\/j.ipm.2007.01.016","volume":"43","author":"D Zajic","year":"2007","unstructured":"Zajic, D., Dorr, B.J., Lin, J., Schwartz, R.: Multi-candidate reduction: sentence compression as a tool for document summarization tasks. Inf. Process. Manag. 43(6), 1549\u20131570 (2007)","journal-title":"Inf. Process. Manag."},{"key":"3_CR36","doi-asserted-by":"crossref","unstructured":"Zhou, Q., Yang, N., Wei, F., Zhou, M.: Selective encoding for abstractive sentence summarization. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, vol. 1: Long Papers), pp. 1095\u20131104 (2017)","DOI":"10.18653\/v1\/P17-1101"}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-73197-7_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,7]],"date-time":"2021-08-07T15:11:57Z","timestamp":1628349117000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-73197-7_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030731960","9783030731977"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-73197-7_3","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 April 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Taipei","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Taiwan","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":"11 April 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 April 2021","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":"dasfaa2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/dm.iis.sinica.edu.tw\/DASFAA2021\/index.html","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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"490","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":"98","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":"33","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":"20% - 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":"4","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":"7","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to the Corona pandemic this event was held virtually.","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)"}}]}}