{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T06:46:56Z","timestamp":1743144416653,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030161415"},{"type":"electronic","value":"9783030161422"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","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":[[2019]]},"DOI":"10.1007\/978-3-030-16142-2_18","type":"book-chapter","created":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T02:50:37Z","timestamp":1554346237000},"page":"225-236","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["User Preference-Aware Review Generation"],"prefix":"10.1007","author":[{"given":"Wei","family":"Wang","sequence":"first","affiliation":[]},{"given":"Hai-Tao","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Hao","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,3,20]]},"reference":[{"key":"18_CR1","doi-asserted-by":"crossref","unstructured":"Bowman, S.R., Vilnis, L., Vinyals, O., Dai, A.M., Jozefowicz, R., Bengio, S.: Generating sentences from a continuous space. CoNLL 2016, p. 10 (2016)","DOI":"10.18653\/v1\/K16-1002"},{"key":"18_CR2","doi-asserted-by":"crossref","unstructured":"Costa, F., Ouyang, S., Dolog, P., Lawlor, A.: Automatic generation of natural language explanations. arXiv preprint arXiv:1707.01561 (2017)","DOI":"10.1145\/3180308.3180366"},{"key":"18_CR3","doi-asserted-by":"crossref","unstructured":"Dai, B., Fidler, S., Urtasun, R., Lin, D.: Towards diverse and natural image descriptions via a conditional GAN. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2970\u20132979 (2017)","DOI":"10.1109\/ICCV.2017.323"},{"key":"18_CR4","doi-asserted-by":"crossref","unstructured":"Dong, L., Huang, S., Wei, F., Lapata, M., Zhou, M., Xu, K.: Learning to generate product reviews from attributes. In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, vol. 1, pp. 623\u2013632 (2017)","DOI":"10.18653\/v1\/E17-1059"},{"key":"18_CR5","doi-asserted-by":"crossref","unstructured":"Ghazvininejad, M., Shi, X., Choi, Y., Knight, K.: Generating topical poetry. In: Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pp. 1183\u20131191 (2016)","DOI":"10.18653\/v1\/D16-1126"},{"key":"18_CR6","unstructured":"Graves, A.: Generating sequences with recurrent neural networks. arXiv preprint arXiv:1308.0850 (2013)"},{"issue":"8","key":"18_CR7","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"key":"18_CR8","doi-asserted-by":"crossref","unstructured":"Li, J., Galley, M., Brockett, C., Spithourakis, G., Gao, J., Dolan, B.: A persona-based neural conversation model. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), vol. 1, pp. 994\u20131003 (2016)","DOI":"10.18653\/v1\/P16-1094"},{"key":"18_CR9","unstructured":"Lipton, Z.C., Vikram, S., McAuley, J.: Capturing meaning in product reviews with character-level generative text models. arXiv preprint arXiv:1511.03683 (2015)"},{"key":"18_CR10","doi-asserted-by":"crossref","unstructured":"McAuley, J., Pandey, R., Leskovec, J.: Inferring networks of substitutable and complementary products. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 785\u2013794. ACM (2015)","DOI":"10.1145\/2783258.2783381"},{"key":"18_CR11","doi-asserted-by":"crossref","unstructured":"Mikolov, T., Karafi\u00e1t, M., Burget, L., \u010cernock\u1ef3, J., Khudanpur, S.: Recurrent neural network based language model. In: Eleventh Annual Conference of the International Speech Communication Association (2010)","DOI":"10.21437\/Interspeech.2010-343"},{"key":"18_CR12","first-page":"234","volume":"12","author":"T Mikolov","year":"2012","unstructured":"Mikolov, T., Zweig, G.: Context dependent recurrent neural network language model. SLT 12, 234\u2013239 (2012)","journal-title":"SLT"},{"key":"18_CR13","doi-asserted-by":"crossref","unstructured":"Papineni, K., Roukos, S., Ward, T., Zhu, W.J.: BLEU: a method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, pp. 311\u2013318. Association for Computational Linguistics (2002)","DOI":"10.3115\/1073083.1073135"},{"key":"18_CR14","unstructured":"Pascanu, R., Mikolov, T., Bengio, Y.: On the difficulty of training recurrent neural networks. In: International Conference on Machine Learning, pp. 1310\u20131318 (2013)"},{"key":"18_CR15","doi-asserted-by":"crossref","unstructured":"Reiter, E., Dale, R.: Building Natural Language Generation Systems. Cambridge University Press (2000)","DOI":"10.1017\/CBO9780511519857"},{"key":"18_CR16","doi-asserted-by":"crossref","unstructured":"Ren, Z., Wang, X., Zhang, N., Lv, X., Li, L.J.: Deep reinforcement learning-based image captioning with embedding reward. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 290\u2013298 (2017)","DOI":"10.1109\/CVPR.2017.128"},{"key":"18_CR17","doi-asserted-by":"crossref","unstructured":"Rennie, S.J., Marcheret, E., Mroueh, Y., Ross, J., Goel, V.: Self-critical sequence training for image captioning. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7008\u20137024 (2017)","DOI":"10.1109\/CVPR.2017.131"},{"key":"18_CR18","unstructured":"Sutskever, I., Martens, J., Hinton, G.E.: Generating text with recurrent neural networks. In: Proceedings of the 28th International Conference on Machine Learning (ICML-11), pp. 1017\u20131024 (2011)"},{"key":"18_CR19","unstructured":"Tang, J., Yang, Y., Carton, S., Zhang, M., Mei, Q.: Context-aware natural language generation with recurrent neural networks. arXiv preprint arXiv:1611.09900 (2016)"},{"issue":"2","key":"18_CR20","first-page":"26","volume":"4","author":"T Tieleman","year":"2012","unstructured":"Tieleman, T., Hinton, G.: Lecture 6.5-RMSProp: divide the gradient by a running average of its recent magnitude. COURSERA Neural Netw. Mach. Learn. 4(2), 26\u201331 (2012)","journal-title":"COURSERA Neural Netw. Mach. Learn."},{"key":"18_CR21","doi-asserted-by":"crossref","unstructured":"Wu, S., Zhang, D., Yang, N., Li, M., Zhou, M.: Sequence-to-dependency neural machine translation. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), vol. 1, pp. 698\u2013707 (2017)","DOI":"10.18653\/v1\/P17-1065"},{"key":"18_CR22","doi-asserted-by":"crossref","unstructured":"Zhang, J., et al.: Flexible and creative Chinese poetry generation using neural memory. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), vol. 1, pp. 1364\u20131373 (2017)","DOI":"10.18653\/v1\/P17-1125"},{"key":"18_CR23","doi-asserted-by":"crossref","unstructured":"Zhang, X., Lapata, M.: Chinese poetry generation with recurrent neural networks. In: EMNLP, pp. 670\u2013680 (2014)","DOI":"10.3115\/v1\/D14-1074"},{"key":"18_CR24","doi-asserted-by":"publisher","first-page":"702","DOI":"10.1109\/ACCESS.2017.2774839","volume":"6","author":"HT Zheng","year":"2018","unstructured":"Zheng, H.T., Wang, W., Chen, W., Sangaiah, A.K.: Automatic generation of news comments based on gated attention neural networks. IEEE Access 6, 702\u2013710 (2018)","journal-title":"IEEE Access"},{"key":"18_CR25","doi-asserted-by":"crossref","unstructured":"Zhou, H., Tu, Z., Huang, S., Liu, X., Li, H., Chen, J.: Chunk-based Bi-scale decoder for neural machine translation. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), vol. 2, pp. 580\u2013586 (2017)","DOI":"10.18653\/v1\/P17-2092"}],"container-title":["Lecture Notes in Computer Science","Advances in Knowledge Discovery and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-16142-2_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T12:19:24Z","timestamp":1709813964000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-16142-2_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030161415","9783030161422"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-16142-2_18","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"20 March 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Macau","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 April 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 April 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.pakdd2019.org","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":"Microsoft Conf. Man. Toolkit CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"542","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":"137","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":"0","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":"25% - 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":"3.79","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":"5.85","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":"In addition, there were 31 PAKDD 2019 Workshops' papers accepted for publication","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)"}}]}}