{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T19:08:01Z","timestamp":1776366481693,"version":"3.51.2"},"reference-count":41,"publisher":"Informa UK Limited","issue":"1","license":[{"start":{"date-parts":[[2023,4,3]],"date-time":"2023-04-03T00:00:00Z","timestamp":1680480000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62076006"],"award-info":[{"award-number":["62076006"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"University Synergy Innovation Programme of Anhui Province","award":["GXXT-2021-008"],"award-info":[{"award-number":["GXXT-2021-008"]}]},{"name":"Anhui Provincial Key R&D Programme","award":["202004b11020029"],"award-info":[{"award-number":["202004b11020029"]}]},{"name":"Scientific Research Fund for Young Teachers of Anhui University of Science & Technology","award":["QNZD2021-02"],"award-info":[{"award-number":["QNZD2021-02"]}]}],"content-domain":{"domain":["www.tandfonline.com"],"crossmark-restriction":true},"short-container-title":["Connection Science"],"published-print":{"date-parts":[[2023,12,31]]},"DOI":"10.1080\/09540091.2023.2189119","type":"journal-article","created":{"date-parts":[[2023,4,4]],"date-time":"2023-04-04T01:00:59Z","timestamp":1680570059000},"update-policy":"https:\/\/doi.org\/10.1080\/tandf_crossmark_01","source":"Crossref","is-referenced-by-count":11,"title":["Lightweight multilayer interactive attention network for aspect-based sentiment analysis"],"prefix":"10.1080","volume":"35","author":[{"given":"Wenjun","family":"Zheng","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Anhui University of Science &amp; Technology, Huainan, People\u2019s Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shunxiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Anhui University of Science &amp; Technology, Huainan, People\u2019s Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheng","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou, People\u2019s Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Anhui University of Science &amp; Technology, Huainan, People\u2019s Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"301","published-online":{"date-parts":[[2023,4,3]]},"reference":[{"key":"e_1_3_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3503044"},{"key":"e_1_3_2_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2015.2443982"},{"key":"e_1_3_2_4_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/d17-1047"},{"key":"e_1_3_2_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-020-02069-5"},{"key":"e_1_3_2_6_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"key":"e_1_3_2_7_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/p14-2009"},{"key":"e_1_3_2_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/s0893-6080(05)80125-x"},{"key":"e_1_3_2_9_1","unstructured":"Glorot X. & Bengio Y. (2010). Understanding the difficulty of training deep feedforward neural networks. In Proceedings of the thirteenth international conference on artificial intelligence and statistics (pp. 249\u2013256). Microtome Publishing."},{"key":"e_1_3_2_10_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93372-6_22"},{"key":"e_1_3_2_12_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/d19-1654"},{"key":"e_1_3_2_13_1","unstructured":"Kingma D. P. & Ba J. (2015 May 7\u20139). Adam: A method for stochastic optimization. 3rd International Conference on Learning Representations San Diego CA United states ."},{"key":"e_1_3_2_14_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"e_1_3_2_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.11.049"},{"key":"e_1_3_2_16_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/568"},{"key":"e_1_3_2_17_1","unstructured":"Mikolov T. Chen K. Corrado G. & Dean J. (2013 May 2-4). Efficient estimation of word representations in vector space. 1st International Conference on Learning Representations Scottsdale AZ United states ."},{"key":"e_1_3_2_18_1","unstructured":"Nair V. & Hinton G. E. (2010). Rectified linear units improve restricted Boltzmann machines. In Proceedings of the 13th International Conference on Artificial Intelligence and Statistics (pp. 249\u2013256). Microtome Publishing."},{"key":"e_1_3_2_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2020.2970399"},{"key":"e_1_3_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/69.917563"},{"key":"e_1_3_2_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.02.034"},{"key":"e_1_3_2_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-30490-4_9"},{"key":"e_1_3_2_23_1","unstructured":"Tang D. Qin B. Feng X. & Liu T. (2016). Effective LSTMs for target-dependent sentiment classification. 26th International Conference on Computational Linguistics COLING 2016 (pp. 3298\u20133307). Association for Computational Linguistics."},{"key":"e_1_3_2_24_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/d16-1021"},{"key":"e_1_3_2_25_1","doi-asserted-by":"crossref","unstructured":"Tang H. Ji D. Li C. & Zhou Q. (2020). Dependency graph enhanced dual-transformer structure for aspect-based sentiment classification. In Proceedings of the 58th annual meeting of the association for computational linguistics (pp. 6578\u20136588). Association for Computational Linguistics.","DOI":"10.18653\/v1\/2020.acl-main.588"},{"key":"e_1_3_2_26_1","unstructured":"Vaswani A. Shazeer N. Parmar N. Uszkoreit J. Jones L. Gomez A. N. & Polosukhin I. (2017). Attention is all you need. 31st Annual Conference on Neural Information Processing Systems NIPS 2017 (pp. 5999\u20136009). Neural information processing systems foundation."},{"key":"e_1_3_2_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.03.092"},{"key":"e_1_3_2_28_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/d16-1058"},{"key":"e_1_3_2_29_1","doi-asserted-by":"publisher","DOI":"10.1080\/09540091.2022.2080183"},{"key":"e_1_3_2_30_1","doi-asserted-by":"publisher","DOI":"10.1080\/09540091.2021.2006146"},{"key":"e_1_3_2_31_1","doi-asserted-by":"crossref","unstructured":"Wu Z. & Ong D. C. (2021). Context-guided bert for targeted aspect-based sentiment analysis. In Proceedings of the AAAI Conference on Artificial Intelligence (pp. 14094\u201314102). Association for the Advancement of Artificial Intelligence.","DOI":"10.1609\/aaai.v35i16.17659"},{"key":"e_1_3_2_32_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-60457-8_45"},{"key":"e_1_3_2_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108586"},{"key":"e_1_3_2_34_1","doi-asserted-by":"publisher","DOI":"10.1080\/09540091.2021.1981825"},{"key":"e_1_3_2_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.01.024"},{"key":"e_1_3_2_36_1","doi-asserted-by":"crossref","unstructured":"Xue W. & Li T. (2018). Aspect based sentiment analysis with gated convolutional networks. In Proceeding of the 56th Annual Meeting of the Association for Computational Linguistics (pp. 2514\u20132523). Association for Computational Linguistics.","DOI":"10.18653\/v1\/P18-1234"},{"key":"e_1_3_2_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.08.001"},{"key":"e_1_3_2_38_1","doi-asserted-by":"publisher","DOI":"10.3390\/app9163389"},{"key":"e_1_3_2_39_1","doi-asserted-by":"publisher","DOI":"10.1002\/widm.1253"},{"key":"e_1_3_2_40_1","doi-asserted-by":"publisher","DOI":"10.1080\/09540091.2021.1985968"},{"key":"e_1_3_2_41_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2203.01054"},{"key":"e_1_3_2_42_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2201.04831"}],"container-title":["Connection Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.tandfonline.com\/doi\/pdf\/10.1080\/09540091.2023.2189119","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,28]],"date-time":"2023-12-28T07:39:41Z","timestamp":1703749181000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/09540091.2023.2189119"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,3]]},"references-count":41,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,12,31]]}},"alternative-id":["10.1080\/09540091.2023.2189119"],"URL":"https:\/\/doi.org\/10.1080\/09540091.2023.2189119","relation":{},"ISSN":["0954-0091","1360-0494"],"issn-type":[{"value":"0954-0091","type":"print"},{"value":"1360-0494","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,3]]},"assertion":[{"value":"The publishing and review policy for this title is described in its Aims & Scope.","order":1,"name":"peerreview_statement","label":"Peer Review Statement"},{"value":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=ccos20","URL":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=ccos20","order":2,"name":"aims_and_scope_url","label":"Aim & Scope"},{"value":"2022-08-12","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-03-06","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-04-03","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"2189119"}}