{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T07:10:02Z","timestamp":1778915402624,"version":"3.51.4"},"reference-count":37,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T00:00:00Z","timestamp":1777939200000},"content-version":"vor","delay-in-days":4,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72101137"],"award-info":[{"award-number":["72101137"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2021MF117"],"award-info":[{"award-number":["ZR2021MF117"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2022QF020"],"award-info":[{"award-number":["ZR2022QF020"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["UIDB\/04152"],"award-info":[{"award-number":["UIDB\/04152"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Concurrency and Computation"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Serving as a subtask of aspect\u2010based sentiment analysis, aspect sentiment triplet extraction (ASTE) enables the extraction of triplets that consist of aspect terms, opinion terms, and sentiment polarities from user reviews. This enables the mining of user preferences and supports merchants in optimizing products and services. However, most existing studies suffer from limitations such as insufficient ability to capture fine\u2010grained sentiments and failure to effectively mine long\u2010range dependencies. To address these limitations, this paper proposes an ASTE model that integrates multi\u2010scale gated convolution and aspect\u2010aware bidirectional Mamba. Specifically, the model designs a multi\u2010scale gated convolution module, which uses a gating mechanism to dynamically adjust weights and leverages multi\u2010scale convolutional layers to enhance the model's capability of capturing fine\u2010grained sentiment features. Subsequently, aspect\u2010aware bidirectional Mamba is introduced, which explicitly focuses on aspect\u2010related information through aspect\u2010aware gating and adopts a bidirectional structure to capture contextual dependencies, thereby effectively capturing long\u2010range dependencies. Then, an adaptive feature fusion module is constructed to aggregate valid information. Results from experiments conducted on the four sub\u2010datasets of ASTE\u2010DATA\u2010V2 reveal that the proposed model outperforms baseline models, thus comprehensively verifying its validity.<\/jats:p>","DOI":"10.1002\/cpe.70745","type":"journal-article","created":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T13:50:47Z","timestamp":1777989047000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrating Multi\u2010Scale Gated Convolution and Aspect\u2010Aware Bidirectional Mamba for Aspect Sentiment Triplet Extraction"],"prefix":"10.1002","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-1316-7841","authenticated-orcid":false,"given":"Wenhao","family":"Zhou","sequence":"first","affiliation":[{"name":"College of Intelligent Equipment, Shandong University of Science and Technology  Taian China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1312-2528","authenticated-orcid":false,"given":"Yinhua","family":"Tian","sequence":"additional","affiliation":[{"name":"College of Intelligent Equipment, Shandong University of Science and Technology  Taian China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chen","family":"Shi","sequence":"additional","affiliation":[{"name":"College of Intelligent Equipment, Shandong University of Science and Technology  Taian China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cong","family":"Liu","sequence":"additional","affiliation":[{"name":"NOVA Information Management School, Universidade Nova de Lisboa  Lisboa Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5586-109X","authenticated-orcid":false,"given":"Yuyue","family":"Du","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Shandong University of Science and Technology  Qingdao China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2026,5,5]]},"reference":[{"key":"e_1_2_9_2_1","first-page":"2979","volume-title":"Proceedings of the Twenty\u2010Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016","author":"Yin Y.","year":"2016"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/583"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2016.06.009"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.296"},{"key":"e_1_2_9_6_1","first-page":"8947","volume-title":"Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP","author":"Veyseh A. 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