{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,1]],"date-time":"2022-04-01T14:39:34Z","timestamp":1648823974364},"reference-count":26,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. As. Lang. Proc."],"published-print":{"date-parts":[[2020,9]]},"abstract":"<jats:p> Aspect-Based Sentiment Analysis (ABSA), a fine-grained task of opinion mining, which aims to extract sentiment of specific target from text, is an important task in many real-world applications, especially in the legal field. Therefore, in this paper, we study the problem of limitation of labeled training data required and ignorance of in-domain knowledge representation for End-to-End Aspect-Based Sentiment Analysis (E2E-ABSA) in legal field. We proposed a new method under deep learning framework, named Semi-ETEKGs, which applied E2E framework using knowledge graph (KG) embedding in legal field after data augmentation (DA). Specifically, we pre-trained the BERT embedding and in-domain KG embedding for unlabeled data and labeled data with case elements after DA, and then we put two embeddings into the E2E framework to classify the polarity of target-entity. Finally, we built a case-related dataset based on a popular benchmark for ABSA to prove the efficiency of Semi-ETEKGs, and experiments on case-related dataset from microblog comments show that our proposed model outperforms the other compared methods significantly. <\/jats:p>","DOI":"10.1142\/s2717554520500125","type":"journal-article","created":{"date-parts":[[2021,3,8]],"date-time":"2021-03-08T15:47:03Z","timestamp":1615218423000},"page":"2050012","source":"Crossref","is-referenced-by-count":0,"title":["Semi-Supervised Aspect-Based Sentiment Analysis for Case-Related Microblog Reviews Using Case Knowledge Graph Embedding"],"prefix":"10.1142","volume":"30","author":[{"given":"Peilian","family":"Zhao","sequence":"first","affiliation":[{"name":"Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Jingming South Road No.727, Chenggong, Kunming, Yunnan 650500, P. R. China"},{"name":"Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming, Yunnan 650500, P. R. China"}]},{"given":"Cunli","family":"Mao","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Jingming South Road No.727, Chenggong, Kunming, Yunnan 650500, P. R. China"},{"name":"Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming, Yunnan 650500, P. R. China"}]},{"given":"Zhengtao","family":"Yu","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Jingming South Road No.727, Chenggong, Kunming, Yunnan 650500, P. R. China"},{"name":"Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming, Yunnan 650500, P. R. China"}]}],"member":"219","published-online":{"date-parts":[[2021,3,6]]},"reference":[{"key":"S2717554520500125BIB001","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D15-1073"},{"key":"S2717554520500125BIB002","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1058"},{"key":"S2717554520500125BIB003","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/568"},{"key":"S2717554520500125BIB004","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1504"},{"key":"S2717554520500125BIB005","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1136"},{"key":"S2717554520500125BIB006","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2920075"},{"key":"S2717554520500125BIB008","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S15-2082"},{"key":"S2717554520500125BIB009","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/S14-2004"},{"key":"S2717554520500125BIB011","first-page":"1643","volume-title":"Proc. Conf. 2013 Empirical Methods in Natural Language Processing","author":"Mitchell M.","year":"2013"},{"key":"S2717554520500125BIB012","doi-asserted-by":"crossref","unstructured":"R. He,  W. S. Lee,  H. T. Ng and  D. Dahlmeier,  Exploiting Document Knowledge for Aspect-Level Sentiment Classification  (ACL, 2017),  pp. 579\u2013585.","DOI":"10.18653\/v1\/P18-2092"},{"key":"S2717554520500125BIB013","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1380"},{"key":"S2717554520500125BIB014","first-page":"3298","volume-title":"Proc. 26th Int. Conf. Computational Linguistics","author":"Tang D.","year":"2016"},{"key":"S2717554520500125BIB015","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1047"},{"key":"S2717554520500125BIB020","first-page":"2324","volume-title":"Proc. 2019 Conf. the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","author":"Xu H.","year":"2019"},{"key":"S2717554520500125BIB024","first-page":"2787","volume-title":"Proc. 26th Int. Conf. Neural Information Processing Systems","author":"Bordes A.","year":"2016"},{"key":"S2717554520500125BIB025","first-page":"1112","volume-title":"Proc. 28th AAAI Conf. Artificial Intelligence","author":"Wang Z.","year":"2014"},{"key":"S2717554520500125BIB026","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-63558-3_13"},{"key":"S2717554520500125BIB029","first-page":"2071","volume-title":"Proc. 33rd Int. Conf. Machine Learning","volume":"48","author":"Trouillon T.","year":"2016"},{"key":"S2717554520500125BIB030","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132961"},{"key":"S2717554520500125BIB032","first-page":"3837","volume-title":"Advances in Neural Information Processing Systems","author":"Deerrard M.","year":"2016"},{"key":"S2717554520500125BIB033","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_21"},{"key":"S2717554520500125BIB036","first-page":"2181","volume-title":"Proc. 29th AAAI Conf. Artificial Intelligence","author":"Lin Y.","year":"2015"},{"key":"S2717554520500125BIB037","first-page":"985","volume-title":"Proc. 30th AAAI Conf. Artificial Intelligence","author":"Ji G.","year":"2016"},{"key":"S2717554520500125BIB039","doi-asserted-by":"publisher","DOI":"10.1207\/s15516709cog1402_1"},{"key":"S2717554520500125BIB040","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1179"},{"key":"S2717554520500125BIB041","first-page":"282","volume-title":"Proc. 18th Int. Conf. Machine Learning","author":"Lafferty J. D.","year":"2001"}],"container-title":["International Journal of Asian Language Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S2717554520500125","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,17]],"date-time":"2021-05-17T07:11:25Z","timestamp":1621235485000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S2717554520500125"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9]]},"references-count":26,"journal-issue":{"issue":"03","published-print":{"date-parts":[[2020,9]]}},"alternative-id":["10.1142\/S2717554520500125"],"URL":"https:\/\/doi.org\/10.1142\/s2717554520500125","relation":{},"ISSN":["2717-5545","2424-791X"],"issn-type":[{"value":"2717-5545","type":"print"},{"value":"2424-791X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9]]}}}