{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T21:39:52Z","timestamp":1742938792250,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":27,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819794393"},{"type":"electronic","value":"9789819794409"}],"license":[{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-97-9440-9_17","type":"book-chapter","created":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T17:02:31Z","timestamp":1730394151000},"page":"211-223","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Knowledge-Enhanced Utterance Domain Classification with\u00a0Keywords-Assisted Concept Denoising Network"],"prefix":"10.1007","author":[{"given":"Peijie","family":"Huang","sequence":"first","affiliation":[]},{"given":"Boxi","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Yuhong","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Weiting","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Jia","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,1]]},"reference":[{"key":"17_CR1","doi-asserted-by":"crossref","unstructured":"Liu, B., Lane, I.: Attention-based recurrent neural network models for joint intent detection and slot filling. In: Proceedings of the 17th Annual Conference of the International Speech Communication Association (INTERSPEECH 2016), pp. 685\u2013689 (2016)","DOI":"10.21437\/Interspeech.2016-1352"},{"key":"17_CR2","doi-asserted-by":"crossref","unstructured":"Vu, N.T., Gupta, P., Adel, H., Sch\u00fctze, H.: Bi-directional recurrent neural network with ranking loss for spoken language understanding. In: Proceedings of the 41st International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), pp. 6060\u20136064 (2016)","DOI":"10.1109\/ICASSP.2016.7472841"},{"key":"17_CR3","doi-asserted-by":"crossref","unstructured":"Kim, Y.B., Kim, D., Kumar, A., Sarikaya, R.: Efficient large-scale neural domain classification with personalized attention. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018), pp. 2214\u20132224 (2018)","DOI":"10.18653\/v1\/P18-1206"},{"key":"17_CR4","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2019), pp. 4171\u20134186 (2019)"},{"key":"17_CR5","unstructured":"Yang, Z., Dai, Z., Yang, Y., Carbonell, J., Salakhutdinov, R., Le, Q.V.: XLNet: generalized autoregressive pretraining for language understanding. In: Proceedings of the 33rd Annual Conference on Neural Information Processing Systems (NeurIPS 2019), pp. 5754\u20135764 (2019)"},{"key":"17_CR6","doi-asserted-by":"crossref","unstructured":"Du, Z., Huang, P., He, Y., Liu, W., Zhu, J.: A knowledge-gated mechanism for utterance domain classification. In: Proceedings of the 8th CCF International Conference on Natural Language Processing and Chinese Computing (NLPCC 2019), pp. 142\u2013154","DOI":"10.1007\/978-3-030-32236-6_12"},{"key":"17_CR7","doi-asserted-by":"crossref","unstructured":"Chen, J., Hu, Y., Liu, J., Xiao, Y., Jiang, H.: Deep short text classification with knowledge powered attention. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI 2019), pp. 6252\u20136259 (2019)","DOI":"10.1609\/aaai.v33i01.33016252"},{"key":"17_CR8","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wang, S., Yao, Q., Dou, D.: Hierarchical heterogeneous graph representation learning for short text classification. In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), pp. 3091\u20133101 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.247"},{"key":"17_CR9","doi-asserted-by":"crossref","unstructured":"Tseng, Y.W., Yang, H.K., Wang, W.Y., Peng, W.C.: KAHAN: knowledge-aware hierarchical attention network for fake news detection on social media. In: Proceedings of the ACM Web Conference 2022 (WWW 2022), pp. 868\u2013875 (2022)","DOI":"10.1145\/3487553.3524664"},{"key":"17_CR10","doi-asserted-by":"crossref","unstructured":"Wang, J., Wang, Z., Zhang, D., Yan, J.: Combining knowledge with deep convolutional neural networks for short text classification. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), vol.\u00a0350, pp. 2915\u20132921 (2017)","DOI":"10.24963\/ijcai.2017\/406"},{"key":"17_CR11","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 2014), pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"},{"key":"17_CR12","unstructured":"Zhang, X., Zhao, J., LeCun, Y.: Character-level convolutional networks for text classification. In: Proceedings of the 28th International Conference on Neural Information Processing Systems (NIPS 2015), vol.\u00a028 (2015)"},{"key":"17_CR13","doi-asserted-by":"crossref","unstructured":"Lai, S., Xu, L., Liu, K., Zhao, J.: Recurrent convolutional neural networks for text classification. In: Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI 2015), pp. 2267\u20132273 (2015)","DOI":"10.1609\/aaai.v29i1.9513"},{"key":"17_CR14","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1007\/978-3-030-32381-3_16","volume-title":"Chinese Computational Linguistics","author":"C Sun","year":"2019","unstructured":"Sun, C., Qiu, X., Xu, Y., Huang, X.: How to fine-tune BERT for text classification? In: Sun, M., Huang, X., Ji, H., Liu, Z., Liu, Y. (eds.) CCL 2019. LNCS (LNAI), vol. 11856, pp. 194\u2013206. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-32381-3_16"},{"key":"17_CR15","unstructured":"OpenAI: GPT-4 technical report (2024)"},{"key":"17_CR16","unstructured":"Touvron, H., Lavril, T., Izacard, G., et\u00a0al.: LLaMA: open and efficient foundation language models. CoRR abs\/2302.13971 (2023)"},{"key":"17_CR17","doi-asserted-by":"crossref","unstructured":"Chen, Q., Ji, F., Chen, H., Zhang, Y.: Improving commonsense question answering by graph-based iterative retrieval over multiple knowledge sources. In: Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), pp. 2583\u20132594 (2020)","DOI":"10.18653\/v1\/2020.coling-main.232"},{"key":"17_CR18","doi-asserted-by":"crossref","unstructured":"Qiu, D., et al.: Machine reading comprehension using structural knowledge graph-aware network. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP 2019), pp. 5896\u20135901 (2019)","DOI":"10.18653\/v1\/D19-1602"},{"key":"17_CR19","doi-asserted-by":"crossref","unstructured":"Ji, H., Ke, P., Huang, S., Wei, F., Zhu, X., Huang, M.: Language generation with multi-hop reasoning on commonsense knowledge graph. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), pp. 725\u2013736 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.54"},{"key":"17_CR20","doi-asserted-by":"crossref","unstructured":"Zeng, J., Li, J., Song, Y., Gao, C., Lyu, M.R., King, I.: Topic memory networks for short text classification. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018), pp. 3120\u20133131 (2018)","DOI":"10.18653\/v1\/D18-1351"},{"key":"17_CR21","doi-asserted-by":"crossref","unstructured":"Chen, J., et al.: CN-Probase: a data-driven approach for large-scale Chinese taxonomy construction. In: Proceedings of the ICDE 2019, pp. 1706\u20131709 (2019)","DOI":"10.1109\/ICDE.2019.00178"},{"key":"17_CR22","unstructured":"Grootendorst, M.: KeyBERT: minimal keyword extraction with BERT. Zenodo:10.5281\/zenodo.4461265 (2020)"},{"key":"17_CR23","doi-asserted-by":"crossref","unstructured":"Yan, X., Guo, J., Lan, Y., Cheng, X.: A biterm topic model for short texts. In: Proceedings of the ACM Web Conference 2013 (WWW 2013), pp. 1445\u20131456 (2013)","DOI":"10.1145\/2488388.2488514"},{"key":"17_CR24","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Proceedings of the 30th International Conference on Neural Information Processing Systems (NIPS 2017), pp. 6000\u20136010 (2017)"},{"key":"17_CR25","unstructured":"Zhang, W., Chen, Z., Che, W., Hu, G., Liu, T.: The first evaluation of Chinese human-computer dialogue technology. CoRR abs\/1709.10217 (2017)"},{"key":"17_CR26","doi-asserted-by":"crossref","unstructured":"Liu, Y., Meng, F., Zhang, J., Zhou, J., Chen, Y., Xu, J.: CM-Net: a novel collaborative memory network for spoken language understanding. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP 2019), pp. 1051\u20131060 (2019)","DOI":"10.18653\/v1\/D19-1097"},{"key":"17_CR27","unstructured":"Li, Z., et al.: Label supervised llama finetuning. CoRR abs\/2310.01208 (2023)"}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Chinese Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-9440-9_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T17:11:16Z","timestamp":1730394676000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-9440-9_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,1]]},"ISBN":["9789819794393","9789819794409"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-9440-9_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,11,1]]},"assertion":[{"value":"1 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLPCC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"CCF International Conference on Natural Language Processing and Chinese Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hangzhou","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":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 November 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 November 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nlpcc2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/tcci.ccf.org.cn\/conference\/2024\/index.php","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}