{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T23:20:45Z","timestamp":1767828045310,"version":"3.49.0"},"reference-count":42,"publisher":"Association for Computing Machinery (ACM)","issue":"6","license":[{"start":{"date-parts":[[2019,10,15]],"date-time":"2019-10-15T00:00:00Z","timestamp":1571097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"crossref","award":["61572376, 91646206"],"award-info":[{"award-number":["61572376, 91646206"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100013314","name":"111 project","doi-asserted-by":"crossref","award":["B07037"],"award-info":[{"award-number":["B07037"]}],"id":[{"id":"10.13039\/501100013314","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Knowl. Discov. Data"],"published-print":{"date-parts":[[2019,12,31]]},"abstract":"<jats:p>\n            Aspect category sentiment analysis (ACSA) is an underexploited subtask in aspect level sentiment analysis. It aims to identify the sentiment of predefined aspect categories. The main challenge in ACSA comes from the fact that the aspect category may not occur in the sentence in most of the cases. For example, the review \u201c\n            <jats:italic>they have delicious sandwiches<\/jats:italic>\n            \u201d positively talks about the aspect category \u201c\n            <jats:italic>food<\/jats:italic>\n            \u201d in an implicit manner.\n          <\/jats:p>\n          <jats:p>\n            In this article, we propose a novel aspect aware learning (AAL) framework for ACSA tasks. Our key idea is to exploit the interaction between the aspect category and the contents under the guidance of both sentiment polarity and predefined categories. To this end, we design a two-way memory network for integrating AAL into the framework of sentiment classification. We further present two algorithms to incorporate the potential impacts of aspect categories. One is to capture the correlations between aspect terms and the aspect category like\n            <jats:italic>\u201csandwiches\u201d<\/jats:italic>\n            and\n            <jats:italic>\u201cfood.\u201d<\/jats:italic>\n            The other is to recognize the aspect category for sentiment representations like\n            <jats:italic>\u201cfood\u201d<\/jats:italic>\n            for\n            <jats:italic>\u201cdelicious.\u201d<\/jats:italic>\n            We conduct extensive experiments on four SemEval datasets. The results reveal the essential role of AAL in ACSA by achieving the state-of-the-art performance.\n          <\/jats:p>","DOI":"10.1145\/3350487","type":"journal-article","created":{"date-parts":[[2019,10,15]],"date-time":"2019-10-15T16:35:58Z","timestamp":1571157358000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":35,"title":["Aspect Aware Learning for Aspect Category Sentiment Analysis"],"prefix":"10.1145","volume":"13","author":[{"given":"Peisong","family":"Zhu","sequence":"first","affiliation":[{"name":"Wuhan University, Wuhan, Hubei, China"}]},{"given":"Zhuang","family":"Chen","sequence":"additional","affiliation":[{"name":"Wuhan University, Wuhan, Hubei, China"}]},{"given":"Haojie","family":"Zheng","sequence":"additional","affiliation":[{"name":"Wuhan University, Wuhan, Hubei, China"}]},{"given":"Tieyun","family":"Qian","sequence":"additional","affiliation":[{"name":"Wuhan University, Wuhan, Hubei, China"}]}],"member":"320","published-online":{"date-parts":[[2019,10,15]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1047"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.5555\/89086.89095"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/P14-2009"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/557"},{"key":"e_1_2_1_5_1","volume-title":"Conference on Empirical Methods in Natural Language Processing (EMNLP\u201916)","author":"Hamilton W. L."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1036"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-2092"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1014052.1014073"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.5555\/2002472.2002492"},{"key":"e_1_2_1_11_1","volume-title":"Conference on Empirical Methods on Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL\u201907)","author":"Kim Soo Min"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00134"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3018661.3018714"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1087"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1310"},{"key":"e_1_2_1_16_1","volume-title":"Sentiment Analysis and Opinion Mining","author":"Liu Bing"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/568"},{"key":"e_1_2_1_18_1","volume-title":"AAAI Conference on Artificial Intelligence.","author":"Ma Yukun","year":"2018"},{"key":"e_1_2_1_19_1","unstructured":"Tomas Mikolov Kai Chen Greg Corrado and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. ICLR (Workshop Poster).  Tomas Mikolov Kai Chen Greg Corrado and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. ICLR (Workshop Poster)."},{"key":"e_1_2_1_20_1","volume-title":"International Workshop on Semantic Evaluation (SemEval\u201913)","author":"Mohammad Saif M.","year":"2013"},{"key":"e_1_2_1_21_1","volume-title":"Annual Conference of the North American Chapter of the Association for Computational Linguistics. 786--794","author":"Nakagawa Tetsuji","year":"2010"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/945645.945658"},{"key":"e_1_2_1_23_1","volume-title":"Conference on Empirical Methods in Natural Language Processing (EMNLP\u201902)","author":"Pang Bo","year":"2002"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1233"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S16-1002"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S15-2082"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/S14-2004"},{"key":"e_1_2_1_29_1","unstructured":"Sainbayar Sukhbaatar Arthur Szlam Jason Weston and Rob Fergus. 2015. End-to-end memory networks. In Advances in Neural Information Processing Systems (NIPS\u201915). 2440--2448.  Sainbayar Sukhbaatar Arthur Szlam Jason Weston and Rob Fergus. 2015. End-to-end memory networks. In Advances in Neural Information Processing Systems (NIPS\u201915). 2440--2448."},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1162\/COLI_a_00049"},{"key":"e_1_2_1_31_1","volume-title":"International Conference on Computational Linguistics (COLING\u201916)","author":"Tang Duyu","year":"2016"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1021"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132936"},{"key":"e_1_2_1_34_1","volume-title":"AAAI Conference on Artificial Intelligence.","author":"Tay Yi","year":"2018"},{"key":"e_1_2_1_35_1","volume-title":"International Joint Conferences on Artificial Intelligence (IJCAI\u201915)","author":"Vo Duy-Tin","year":"2015"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1052"},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1088"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1059"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1058"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1234"},{"key":"e_1_2_1_41_1","volume-title":"AAAI Conference on Artificial Intelligence.","author":"Yang Jun","year":"2018"},{"key":"e_1_2_1_42_1","volume-title":"International Conference on Computational Linguistics (COLING\u201918)","author":"Zhu Peisong","year":"2018"}],"container-title":["ACM Transactions on Knowledge Discovery from Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3350487","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3350487","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:23:20Z","timestamp":1750202600000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3350487"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,15]]},"references-count":42,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2019,12,31]]}},"alternative-id":["10.1145\/3350487"],"URL":"https:\/\/doi.org\/10.1145\/3350487","relation":{},"ISSN":["1556-4681","1556-472X"],"issn-type":[{"value":"1556-4681","type":"print"},{"value":"1556-472X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,10,15]]},"assertion":[{"value":"2018-12-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-07-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-10-15","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}