{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T11:11:24Z","timestamp":1726053084063},"publisher-location":"Cham","reference-count":20,"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_4","type":"book-chapter","created":{"date-parts":[[2019,9,29]],"date-time":"2019-09-29T19:23:57Z","timestamp":1569785037000},"page":"41-52","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Document-Based Question Answering Improves Query-Focused Multi-document Summarization"],"prefix":"10.1007","author":[{"given":"Weikang","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingxing","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunfang","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Furu","family":"Wei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,9,30]]},"reference":[{"key":"4_CR1","unstructured":"Baumel, T., Eyal, M., Elhadad, M.: Query focused abstractive summarization: Incorporating query relevance, multi-document coverage, and summary length constraints into seq2seq models. arXiv preprint \n                      arXiv:1801.07704\n                      \n                     (2018)"},{"key":"4_CR2","unstructured":"Cao, Z., Li, W., Li, S., Wei, F.: Attsum: Joint learning of focusing and summarization with neural attention. CoRR abs\/1604.00125 (2016). \n                      http:\/\/arxiv.org\/abs\/1604.00125"},{"key":"4_CR3","doi-asserted-by":"crossref","unstructured":"Cao, Z., Wei, F., Li, S., Li, W., Zhou, M., Houfeng, W.: Learning summary prior representation for extractive summarization. In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), vol. 2, pp. 829\u2013833 (2015)","DOI":"10.3115\/v1\/P15-2136"},{"key":"4_CR4","doi-asserted-by":"crossref","unstructured":"Carbonell, J., Goldstein, J.: The use of mmr, diversity-based reranking for reordering documents and producing summaries. In: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 335\u2013336. ACM (1998)","DOI":"10.1145\/290941.291025"},{"key":"4_CR5","doi-asserted-by":"crossref","unstructured":"Cho, K., et al.: Learning phrase representations using rnn encoder-decoder for statistical machine translation. arXiv preprint \n                      arXiv:1406.1078\n                      \n                     (2014)","DOI":"10.3115\/v1\/D14-1179"},{"key":"4_CR6","doi-asserted-by":"crossref","unstructured":"Gu, J., Wang, Y., Chen, Y., Cho, K., Li, V.O.: Meta-learning for low-resource neural machine translation. arXiv preprint \n                      arXiv:1808.08437\n                      \n                     (2018)","DOI":"10.18653\/v1\/D18-1398"},{"key":"4_CR7","doi-asserted-by":"crossref","unstructured":"Jurczyk, T., Zhai, M., Choi, J.D.: Selqa: A new benchmark for selection-based question answering. In: 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI), pp. 820\u2013827. IEEE (2016)","DOI":"10.1109\/ICTAI.2016.0128"},{"key":"4_CR8","unstructured":"Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. arXiv preprint \n                      arXiv:1412.6980\n                      \n                     (2014)"},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Kobayashi, H., Noguchi, M., Yatsuka, T.: Summarization based on embedding distributions. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 1984\u20131989 (2015)","DOI":"10.18653\/v1\/D15-1232"},{"key":"4_CR10","doi-asserted-by":"crossref","unstructured":"Lebanoff, L., Song, K., Liu, F.: Adapting the neural encoder-decoder framework from single to multi-document summarization. arXiv preprint \n                      arXiv:1808.06218\n                      \n                     (2018)","DOI":"10.18653\/v1\/D18-1446"},{"key":"4_CR11","unstructured":"Li, C., Qian, X., Liu, Y.: Using supervised bigram-based ILP for extractive summarization. In: Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), vol. 1, pp. 1004\u20131013 (2013)"},{"key":"4_CR12","doi-asserted-by":"crossref","unstructured":"Luong, M.T., Pham, H., Manning, C.D.: Effective approaches to attention-based neural machine translation. arXiv preprint \n                      arXiv:1508.04025\n                      \n                     (2015)","DOI":"10.18653\/v1\/D15-1166"},{"key":"4_CR13","doi-asserted-by":"crossref","unstructured":"Ouyang, Y., Li, S., Li, W.: Developing learning strategies for topic-based summarization. In: Proceedings of the Sixteenth ACM Conference on Conference on Information and Knowledge Management, pp. 79\u201386. ACM (2007)","DOI":"10.1145\/1321440.1321454"},{"issue":"2","key":"4_CR14","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1016\/j.ipm.2010.03.005","volume":"47","author":"Y Ouyang","year":"2011","unstructured":"Ouyang, Y., Li, W., Li, S., Lu, Q.: Applying regression models to query-focused multi-document summarization. Inf. Process. Manage. 47(2), 227\u2013237 (2011)","journal-title":"Inf. Process. Manage."},{"key":"4_CR15","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":"4_CR16","doi-asserted-by":"crossref","unstructured":"Rajpurkar, P., Zhang, J., Lopyrev, K., Liang, P.: Squad: 100,000+ questions for machine comprehension of text. arXiv preprint \n                      arXiv:1606.05250\n                      \n                     (2016)","DOI":"10.18653\/v1\/D16-1264"},{"key":"4_CR17","doi-asserted-by":"publisher","unstructured":"Ren, P., Chen, Z., Ren, Z., Wei, F., Ma, J., de Rijke, M.: Leveraging contextual sentence relations for extractive summarization using a neural attention model. In: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2017, pp. 95\u2013104. ACM, New York, NY, USA (2017). \n                      https:\/\/doi.org\/10.1145\/3077136.3080792\n                      \n                    , \n                      http:\/\/doi.acm.org\/10.1145\/3077136.3080792","DOI":"10.1145\/3077136.3080792"},{"key":"4_CR18","doi-asserted-by":"crossref","unstructured":"Wan, X., Xiao, J.: Graph-based multi-modality learning for topic-focused multi-document summarization. In: IJCAI, pp. 1586\u20131591 (2009)","DOI":"10.1145\/1645953.1646184"},{"key":"4_CR19","doi-asserted-by":"crossref","unstructured":"Wasson, M.: Using leading text for news summaries: evaluation results and implications for commercial summarization applications. In: Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics, vol. 2 pp. 1364\u20131368. Association for Computational Linguistics (1998)","DOI":"10.3115\/980432.980791"},{"key":"4_CR20","unstructured":"Zhang, J., Tan, J., Wan, X.: Towards a neural network approach to abstractive multi-document summarization. arXiv preprint \n                      arXiv:1804.09010\n                      \n                     (2018)"}],"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_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,29]],"date-time":"2019-09-29T19:42:22Z","timestamp":1569786142000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-32236-6_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030322359","9783030322366"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-32236-6_4","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)"}}]}}