{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T09:22:10Z","timestamp":1743067330830,"version":"3.40.3"},"publisher-location":"Cham","reference-count":36,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030594121"},{"type":"electronic","value":"9783030594138"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-59413-8_8","type":"book-chapter","created":{"date-parts":[[2020,9,21]],"date-time":"2020-09-21T16:54:52Z","timestamp":1600707292000},"page":"93-105","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Two-Level Convolutional Neural Network for Aspect Extraction"],"prefix":"10.1007","author":[{"given":"Jialin","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Cai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingbao","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyun","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Raymond Chi-Wing","family":"Wong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,9,22]]},"reference":[{"key":"8_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-007-5070-8","volume-title":"Sentic Computing: Techniques, Tools, and Applications","author":"E Cambria","year":"2012","unstructured":"Cambria, E., Hussain, A.: Sentic Computing: Techniques, Tools, and Applications, vol. 2. Springer Science & Business Media, Heidelberg (2012)"},{"unstructured":"Gehring, J., Auli, M., Grangier, D., Yarats, D., Dauphin, Y.N.: Convolutional sequence to sequence learning (2017)","key":"8_CR2"},{"doi-asserted-by":"crossref","unstructured":"He, R., Lee, W.S., Ng, H.T., Dahlmeier, D.: An unsupervised neural attention model for aspect extraction. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). vol. 1, pp. 388\u2013397 (2017)","key":"8_CR3","DOI":"10.18653\/v1\/P17-1036"},{"unstructured":"Hochreiter, S., Schmidhuber, J.: LSTM can solve hard long time lag problems. In: Advances in Neural Information Processing Systems, pp. 473\u2013479 (1997)","key":"8_CR4"},{"doi-asserted-by":"crossref","unstructured":"Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Seattle, Washington, USA, pp. 168\u2013177, August 2004","key":"8_CR5","DOI":"10.1145\/1014052.1014073"},{"unstructured":"Jakob, N., Gurevych, I.: Extracting opinion targets in a single- and cross-domain setting with conditional random fields. In: Conference on Empirical Methods in Natural Language Processing, pp. 1035\u20131045 (2010)","key":"8_CR6"},{"doi-asserted-by":"crossref","unstructured":"Jebbara, S., Cimiano, P.: Improving opinion-target extraction with character-level word embeddings (2017)","key":"8_CR7","DOI":"10.18653\/v1\/W17-4124"},{"doi-asserted-by":"crossref","unstructured":"Kim, Y.: Convolutional neural networks for sentence classification. Eprint Arxiv (2014)","key":"8_CR8","DOI":"10.3115\/v1\/D14-1181"},{"unstructured":"Lafferty, J., McCallum, A., Pereira, F.C.: Conditional random fields: Probabilistic models for segmenting and labeling sequence data (2001)","key":"8_CR9"},{"key":"8_CR10","volume-title":"Convolutional Networks for Images, Speech, and Time Series","author":"Y Lecun","year":"1998","unstructured":"Lecun, Y., Bengio, Y.: Convolutional Networks for Images, Speech, and Time Series. MIT Press, Cambridge (1998)"},{"doi-asserted-by":"crossref","unstructured":"Li, X., Lam, W.: Deep multi-task learning for aspect term extraction with memory interaction. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 2886\u20132892 (2017)","key":"8_CR11","DOI":"10.18653\/v1\/D17-1310"},{"doi-asserted-by":"crossref","unstructured":"Lin, C., He, Y.: Joint sentiment\/topic model for sentiment analysis. In: ACM Conference on Information & Knowledge Management, pp. 375\u2013384 (2009)","key":"8_CR12","DOI":"10.1145\/1645953.1646003"},{"issue":"1","key":"8_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2200\/S00416ED1V01Y201204HLT016","volume":"5","author":"B Liu","year":"2012","unstructured":"Liu, B.: Sentiment analysis and opinion mining. Synth. Lect. Hum. Lang. Technol. 5(1), 1\u2013167 (2012)","journal-title":"Synth. Lect. Hum. Lang. Technol."},{"doi-asserted-by":"crossref","unstructured":"Liu, P., Joty, S., Meng, H.: Fine-grained opinion mining with recurrent neural networks and word embeddings. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 1433\u20131443 (2015)","key":"8_CR14","DOI":"10.18653\/v1\/D15-1168"},{"doi-asserted-by":"crossref","unstructured":"Ma, X., Hovy, E.: End-to-end sequence labeling via bi-directional lstm-cnns-crf. arXiv preprint arXiv:1603.01354 (2016)","key":"8_CR15","DOI":"10.18653\/v1\/P16-1101"},{"key":"8_CR16","first-page":"2579","volume":"9","author":"LVD Maaten","year":"2008","unstructured":"Maaten, L.V.D., Hinton, G.: Visualizing data using t-SNE. J. Mach. Learn. Res. 9, 2579\u20132605 (2008)","journal-title":"J. Mach. Learn. Res."},{"doi-asserted-by":"crossref","unstructured":"Mei, Q., Ling, X., Wondra, M., Su, H., Zhai, C.X.: Topic sentiment mixture: modeling facets and opinions in weblogs. In: International Conference on World Wide Web, pp. 171\u2013180 (2007)","key":"8_CR17","DOI":"10.1145\/1242572.1242596"},{"unstructured":"Mitchell, M., Aguilar, J., Wilson, T., Van Durme, B.: Open domain targeted sentiment. In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pp. 1643\u20131654 (2013)","key":"8_CR18"},{"doi-asserted-by":"crossref","unstructured":"Moghaddam, S., Ester, M.: ILDA: interdependent LDA model for learning latent aspects and their ratings from online product reviews. In: Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 665\u2013674 (2011)","key":"8_CR19","DOI":"10.1145\/2009916.2010006"},{"issue":"1","key":"8_CR20","first-page":"1","volume":"2","author":"B Pang","year":"2008","unstructured":"Pang, B., L, Lee., et al.: Opinion mining and sentiment analysis. Found. Trends\u00ae Inf. Retrieval 2(1), 1\u2013135 (2008)","journal-title":"Found. Trends\u00ae Inf. Retrieval"},{"doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., Manning, C.: Glove: global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1532\u20131543 (2014)","key":"8_CR21","DOI":"10.3115\/v1\/D14-1162"},{"doi-asserted-by":"crossref","unstructured":"Popescu, A.M.: Extracting product features and opinions from reviews. In: HLT\/EMNLP on Interactive Demonstrations, pp. 32\u201333 (2005)","key":"8_CR22","DOI":"10.3115\/1220575.1220618"},{"key":"8_CR23","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.knosys.2016.06.009","volume":"108","author":"S Poria","year":"2016","unstructured":"Poria, S., Cambria, E., Gelbukh, A.: Aspect extraction for opinion mining with a deep convolutional neural network. Knowl. Based Syst. 108, 42\u201349 (2016)","journal-title":"Knowl. Based Syst."},{"issue":"1","key":"8_CR24","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1162\/coli_a_00034","volume":"37","author":"G Qiu","year":"2011","unstructured":"Qiu, G., Liu, B., Bu, J., Chen, C.: Opinion word expansion and target extraction through double propagation. Comput. Linguist. 37(1), 9\u201327 (2011)","journal-title":"Comput. Linguist."},{"issue":"2","key":"8_CR25","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/5.18626","volume":"77","author":"LR Rabiner","year":"1989","unstructured":"Rabiner, L.R.: A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE 77(2), 257\u2013286 (1989)","journal-title":"Proc. IEEE"},{"doi-asserted-by":"crossref","unstructured":"Reimers, N., Gurevych, I.: Reporting score distributions makes a difference: performance study of LSTM-networks for sequence tagging (2017)","key":"8_CR26","DOI":"10.18653\/v1\/D17-1035"},{"doi-asserted-by":"crossref","unstructured":"Shu, L., Xu, H., Liu, B.: Lifelong learning crf for supervised aspect extraction (2017)","key":"8_CR27","DOI":"10.18653\/v1\/P17-2023"},{"unstructured":"Titov, I., McDonald, R.: A joint model of text and aspect ratings for sentiment summarization. In: Proceedings of ACL-08: HLT, pp. 308\u2013316 (2008)","key":"8_CR28"},{"unstructured":"Turian, J., Ratinov, L., Bengio, Y.: Word representations: a simple and general method for semi-supervised learning. In: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pp. 384\u2013394. Association for Computational Linguistics (2010)","key":"8_CR29"},{"doi-asserted-by":"crossref","unstructured":"Wang, B., Wang, H.: Bootstrapping both product features and opinion words from Chinese customer reviews with cross-inducing. In: Proceedings of the Third International Joint Conference on Natural Language Processing: Volume-I (2008)","key":"8_CR30","DOI":"10.1109\/WI.2007.138"},{"doi-asserted-by":"crossref","unstructured":"Wang, W., Pan, S.J., Dahlmeier, D., Xiao, X.: Recursive neural conditional random fields for aspect-based sentiment analysis (2016)","key":"8_CR31","DOI":"10.18653\/v1\/D16-1059"},{"doi-asserted-by":"crossref","unstructured":"Wang, W., Pan, S.J., Dahlmeier, D., Xiao, X.: Coupled multi-layer attentions for co-extraction of aspect and opinion terms. In: AAAI, pp. 3316\u20133322 (2017)","key":"8_CR32","DOI":"10.1609\/aaai.v31i1.10974"},{"unstructured":"Yin, Y., Wei, F., Dong, L., Xu, K., Zhang, M., Zhou, M.: Unsupervised word and dependency path embeddings for aspect term extraction, pp. 2979\u20132985 (2016)","key":"8_CR33"},{"unstructured":"Zhang, X., Zhao, J., Lecun, Y.: Character-level convolutional networks for text classification. In: Advances in Neural Information Processing Systems, pp. 649\u2013657 (2015)","key":"8_CR34"},{"unstructured":"Zhou, X., Wan, X., Xiao, J.: Collective opinion target extraction in Chinese microblogs. In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pp. 1840\u20131850 (2013)","key":"8_CR35"},{"doi-asserted-by":"crossref","unstructured":"Zhuang, L., Jing, F., Zhu, X.Y.: Movie review mining and summarization. In: Proceedings of the 15th ACM International Conference on Information and Knowledge Management, pp. 43\u201350 (2006)","key":"8_CR36","DOI":"10.1145\/1183614.1183625"}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications. DASFAA 2020 International Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-59413-8_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T13:24:51Z","timestamp":1710249891000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-59413-8_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030594121","9783030594138"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-59413-8_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"22 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jeju","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/db.pknu.ac.kr\/dasfaa2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"487","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"119","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"23","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.11","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6.81","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"15 demo papers and 4 industrial papers","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}