{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T07:01:47Z","timestamp":1760598107472,"version":"3.40.3"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030922375"},{"type":"electronic","value":"9783030922382"}],"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\/978-3-030-92238-2_43","type":"book-chapter","created":{"date-parts":[[2021,12,4]],"date-time":"2021-12-04T22:02:35Z","timestamp":1638655355000},"page":"520-531","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["BERTDAN: Question-Answer Dual Attention Fusion Networks with\u00a0Pre-trained Models for\u00a0Answer Selection"],"prefix":"10.1007","author":[{"given":"Haitian","family":"Yang","sequence":"first","affiliation":[]},{"given":"Chonghui","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Xuan","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Yan","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Zheng","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Chao","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Qi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Weiqing","family":"Huang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,12,5]]},"reference":[{"key":"43_CR1","unstructured":"Roth, D.: Learning to resolve natural language ambiguities: a unified approach. In: AAAI\/IAAI 1998, pp. 806\u2013813 (1998)"},{"issue":"3","key":"43_CR2","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1007\/s10791-005-6995-3","volume":"8","author":"D Metzler","year":"2005","unstructured":"Metzler, D., Croft, W.B.: Analysis of statistical question classification for fact-based questions. Inf. Retr. 8(3), 481\u2013504 (2005)","journal-title":"Inf. Retr."},{"key":"43_CR3","doi-asserted-by":"crossref","unstructured":"Barr\u00f3n-Cedeno, A., et al.: Thread-level information for comment classification in community question answering. In: ACL, pp. 687\u2013693, Beijing, China (2015)","DOI":"10.3115\/v1\/P15-2113"},{"key":"43_CR4","doi-asserted-by":"crossref","unstructured":"Joty, S., M\u00e0rquez, L., Nakov, P.: Joint learning with global inference for comment classification in community question answering. In: ACL, pp. 703\u2013713, San Diego, California (2016)","DOI":"10.18653\/v1\/N16-1084"},{"key":"43_CR5","doi-asserted-by":"crossref","unstructured":"Yang, M., et al.: Knowledge-enhanced hierarchical attention for community question answering with multi-task and adaptive learning, pp. 5349\u20135355. In: IJCAI (2019)","DOI":"10.24963\/ijcai.2019\/743"},{"key":"43_CR6","doi-asserted-by":"crossref","unstructured":"Deng, Y., et al.: Joint learning of answer selection and answer summary generation in community question answering, pp. 7651\u20137658. In: AAAI (2020)","DOI":"10.1609\/aaai.v34i05.6266"},{"key":"43_CR7","doi-asserted-by":"crossref","unstructured":"Xie, Y., Shen, Y., et al.: Attentive user-engaged adversarial neural network for community question answering. In: AAAI, vol. 34, pp. 9322\u20139329 (2020)","DOI":"10.1609\/aaai.v34i05.6472"},{"key":"43_CR8","doi-asserted-by":"crossref","unstructured":"Garg, S., Thuy, V., Moschitti, A.: Tanda: transfer and adapt pre-trained transformer models for answer sentence selection. In: AAAI, vol. 34, pp. 7780\u20137788 (2020)","DOI":"10.1609\/aaai.v34i05.6282"},{"key":"43_CR9","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1016\/j.knosys.2019.02.006","volume":"171","author":"M Yang","year":"2019","unstructured":"Yang, M., Wenting, T., Qiang, Q., et al.: Advanced community question answering by leveraging external knowledge and multi-task learning. Knowl.-Based Syst. 171, 106\u2013119 (2019)","journal-title":"Knowl.-Based Syst."},{"key":"43_CR10","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1007\/978-3-030-67664-3_35","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"H Yang","year":"2021","unstructured":"Yang, H., et al.: AMQAN: adaptive multi-attention question-answer networks for answer selection. In: Hutter, F., Kersting, K., Lijffijt, J., Valera, I. (eds.) ECML PKDD 2020. LNCS (LNAI), vol. 12459, pp. 584\u2013599. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-67664-3_35"},{"key":"43_CR11","doi-asserted-by":"crossref","unstructured":"Wan, S., Lan, Y., Guo, J., et al.: A deep architecture for semantic matching with multiple positional sentence representations. In: AAAI, pp. 2835\u20132841 (2016)","DOI":"10.1609\/aaai.v30i1.10342"},{"key":"43_CR12","doi-asserted-by":"crossref","unstructured":"Zhang, X., Li, S., Sha, L., Wang, H.: Attentive interactive neural networks for answer selection in community question answering. In: AAAI, vol. 31 (2017)","DOI":"10.1609\/aaai.v31i1.11006"},{"key":"43_CR13","unstructured":"Devlin, J., Chang, M.W., et al.: Bert: pre-training of deep bidirectional transformers for language understanding. In: NAACL (2019)"},{"key":"43_CR14","unstructured":"Yu, A.W., et al.: Fast and accurate reading comprehension by combining self-attention and convolution. In: ICLR (2018)"},{"key":"43_CR15","unstructured":"Lin, Z., et al.: A structured self-attentive sentence embedding. In: ICLR (2017)"},{"key":"43_CR16","doi-asserted-by":"crossref","unstructured":"Chen, Q., et al.: Enhanced lstm for natural language inference[c]. In: ACL, pp. 1657\u20131668 (2017)","DOI":"10.18653\/v1\/P17-1152"},{"key":"43_CR17","doi-asserted-by":"crossref","unstructured":"Mou, L., et al.: Natural language inference by tree-based convolution and heuristic matching[c]. In: ACL, pp. 130\u2013136 (2016)","DOI":"10.18653\/v1\/P16-2022"},{"key":"43_CR18","unstructured":"Ba, J., Kingma, D.P.: Adam: a method for stochastic optimization. In: ICLR (2015)"},{"key":"43_CR19","doi-asserted-by":"crossref","unstructured":"Tran, Q.H., Tran, D.V., Vu, T., Le Nguyen, M., Pham, S.B.: Jaist: combining multiple features for answer selection in community question answering. In: SemEval-2015, pp. 215\u2013219, Denver, Colorado (2015)","DOI":"10.18653\/v1\/S15-2038"},{"key":"43_CR20","doi-asserted-by":"crossref","unstructured":"Wu, W., Wang, H., Li, S.: Bi-directional gated memory networks for answer selection. In: Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data, pp. 251\u2013262 (2017)","DOI":"10.1007\/978-3-319-69005-6_21"},{"key":"43_CR21","doi-asserted-by":"crossref","unstructured":"Wu, G., Sheng, Y., Lan, M., Wu, Y.: Ecnu at semeval2017 task 3: using traditional and deep learning methods to address community question answering task. In: SemEval-2017, pp. 365\u2013369 (2017)","DOI":"10.18653\/v1\/S17-2060"},{"key":"43_CR22","unstructured":"Xiang, Y., Zhou, X., et al.: Incorporating label dependency for answer quality tagging in community question answering via cnn-lstm-crf. In: COLING, pp. 1231\u20131241, Osaka, Japan (2016)"},{"key":"43_CR23","doi-asserted-by":"crossref","unstructured":"Wu, W., Sun, X., Wang, H., et al.: Question condensing networks for answer selection in community question answering. In: ACL, pp. 1746\u20131755 (2018)","DOI":"10.18653\/v1\/P18-1162"}],"container-title":["Lecture Notes in Computer Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-92238-2_43","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T19:57:00Z","timestamp":1726257420000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-92238-2_43"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030922375","9783030922382"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-92238-2_43","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":"5 December 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sanur, Bali","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Indonesia","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":"8 December 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iconip2021.apnns.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1093","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":"226","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":"177","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":"21% - 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":"2.57","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":"6","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 COVID-19 pandemic the conference was held online.","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)"}}]}}