{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T05:34:00Z","timestamp":1769751240971,"version":"3.49.0"},"reference-count":42,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key R&D Program of China","award":["2019YFF0303001"],"award-info":[{"award-number":["2019YFF0303001"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61871358"],"award-info":[{"award-number":["61871358"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1636201"],"award-info":[{"award-number":["U1636201"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Science and Technology Project of Anhui Province","award":["17030901005"],"award-info":[{"award-number":["17030901005"]}]},{"name":"28th ACM International Conference on Information and Knowledge Management, Beijing, China"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE\/ACM Trans. Audio Speech Lang. Process."],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/taslp.2019.2955290","type":"journal-article","created":{"date-parts":[[2019,11,22]],"date-time":"2019-11-22T21:18:50Z","timestamp":1574457530000},"page":"369-379","source":"Crossref","is-referenced-by-count":22,"title":["Utterance-to-Utterance Interactive Matching Network for Multi-Turn Response Selection in Retrieval-Based Chatbots"],"prefix":"10.1109","volume":"28","author":[{"given":"Jia-Chen","family":"Gu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7853-5273","authenticated-orcid":false,"given":"Zhen-Hua","family":"Ling","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","first-page":"3111","article-title":"Distributed representations of words and phrases and their compositionality","author":"mikolov","year":"0","journal-title":"Proc Advances Neural Inf Process Syst"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"ref33","article-title":"A compare-aggregate model for matching text sequences","volume":"abs 1611 1747","author":"wang","year":"2016","journal-title":"CoRR"},{"key":"ref32","article-title":"Sentence pair scoring: Towards unified framework for text comprehension","volume":"abs 1603 6127","author":"baudis","year":"2016","journal-title":"CoRR"},{"key":"ref31","first-page":"2922","article-title":"Match-srnn: Modeling the recursive matching structure with spatial RNN","author":"wan","year":"2016","journal-title":"Proc 25th Int Joint Conf Artif Intell"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-1170"},{"key":"ref37","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref36","article-title":"Adam: A method for stochastic optimization","volume":"abs 1412 6980","author":"kingma","year":"2014","journal-title":"CoRR"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-1142"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/579"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.5087\/dad.2017.102"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-2028"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1046"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1103"},{"key":"ref13","first-page":"3740","article-title":"Modeling multi-turn conversation with deep utterance aggregation","author":"zhang","year":"2018","journal-title":"Proc 27th Int Conf Comput Linguist"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1193"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1152"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1366"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/721"},{"key":"ref18","first-page":"935","article-title":"A dataset for research on short-text conversations","author":"wang","year":"2013","journal-title":"Proc Conf Empir Methods Natural Lang Process"},{"key":"ref19","article-title":"An information retrieval approach to short text conversation","volume":"abs 1408 6988","author":"ji","year":"2014","journal-title":"CoRR"},{"key":"ref28","first-page":"77","article-title":"The TREC-8 question answering track report","author":"voorhees","year":"1999","journal-title":"Proc 8th Text Retrieval Conf"},{"key":"ref4","article-title":"Building sequential inference models for end-to-end response selection","volume":"abs 1812 686","author":"gu","year":"2018","journal-title":"CoRR"},{"key":"ref27","author":"baeza-yates","year":"1999","journal-title":"Modern Information Retrieval"},{"key":"ref3","first-page":"4970","article-title":"Augmenting end-to-end dialogue systems with commonsense knowledge","author":"young","year":"2018","journal-title":"Proc 32nd AAAI Conf Artif Intell 30th Innovative Appl Artif Intell 8th AAAI Symp Educ Adv Artif Intell"},{"key":"ref6","first-page":"3776","article-title":"Building end-to-end dialogue systems using generative hierarchical neural network models","author":"serban","year":"2016","journal-title":"Proc 30th AAAI Conf Artif Intell"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2911542"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/P15-1152"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"285","DOI":"10.18653\/v1\/W15-4640","article-title":"The Ubuntu Dialogue Corpus: A large dataset for research in unstructured multi-turn dialogue systems","author":"lowe","year":"2015","journal-title":"Proc SIGDIAL Conf The 10th Ann Meeting the Special Interest Group on Discourse and Dialogue"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-018-0598-6"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3166054.3166058"},{"key":"ref9","article-title":"Improved deep learning baselines for Ubuntu Corpus Dialogs","volume":"abs 1510 3753","author":"kadlec","year":"2015","journal-title":"CoRR"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3358140"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1036"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1018"},{"key":"ref21","article-title":"Enhance word representation for out-of-vocabulary on ubuntu dialogue corpus","volume":"abs 1802 2614","author":"dong","year":"2018","journal-title":"CoRR"},{"key":"ref42","first-page":"265","article-title":"Tensorflow: A system for large-scale machine learning","author":"abadi","year":"0","journal-title":"Proc USENIX Symp Operat Syst Des Implement"},{"key":"ref24","article-title":"QANet: Combining local convolution with global self-attention for reading comprehension","author":"yu","year":"2018","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref41","first-page":"807","article-title":"Rectified linear units improve restricted boltzmann machines","author":"nair","year":"2010","journal-title":"Proc 27th Int Conf Mach Learn"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref26","article-title":"Incorporating loose-structured knowledge into LSTM with recall gate for conversation modeling","volume":"abs 1605 5110","author":"xu","year":"2016","journal-title":"CoRR"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33016489"}],"container-title":["IEEE\/ACM Transactions on Audio, Speech, and Language Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6570655\/8938144\/08910440.pdf?arnumber=8910440","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T17:31:21Z","timestamp":1651080681000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8910440\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":42,"URL":"https:\/\/doi.org\/10.1109\/taslp.2019.2955290","relation":{},"ISSN":["2329-9290","2329-9304"],"issn-type":[{"value":"2329-9290","type":"print"},{"value":"2329-9304","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}