{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:45:54Z","timestamp":1742913954171,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":24,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819608492"},{"type":"electronic","value":"9789819608508"}],"license":[{"start":{"date-parts":[[2024,12,24]],"date-time":"2024-12-24T00:00:00Z","timestamp":1734998400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,24]],"date-time":"2024-12-24T00:00:00Z","timestamp":1734998400000},"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\/978-981-96-0850-8_4","type":"book-chapter","created":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T04:39:39Z","timestamp":1734928779000},"page":"49-64","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["UID-Net: Enhancing Click-Through Rate Prediction in\u00a0Trigger-Induced Recommendation Through User Interest Decomposition"],"prefix":"10.1007","author":[{"given":"Jiazhen","family":"Lou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhao","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Wen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingsong","family":"Lv","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fuyu","family":"Lv","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zulong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jia","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,24]]},"reference":[{"key":"4_CR1","doi-asserted-by":"crossref","unstructured":"Guo, H., Tang, R., Ye, Y., Li, Z., He, X.: Deepfm: a factorization-machine based neural network for ctr prediction. arXiv preprint arXiv:1703.04247 (2017)","DOI":"10.24963\/ijcai.2017\/239"},{"issue":"23","key":"4_CR2","first-page":"1","volume":"21","author":"J Guo","year":"2020","unstructured":"Guo, J., He, H., He, T., Lausen, L., Li, M., Lin, H., Shi, X., Wang, C., Xie, J., Zha, S., et al.: Gluoncv and gluonnlp: Deep learning in computer vision and natural language processing. J. Mach. Learn. Res. 21(23), 1\u20137 (2020)","journal-title":"J. Mach. Learn. Res."},{"key":"4_CR3","doi-asserted-by":"crossref","unstructured":"Li, C., Liu, Z., Wu, M., Xu, Y., Zhao, H., Huang, P., Kang, G., Chen, Q., Li, W., Lee, D.L.: Multi-interest network with dynamic routing for recommendation at tmall. In: Proceedings of the 28th ACM International Conference on Information and Knowledge Management. pp. 2615\u20132623 (2019)","DOI":"10.1145\/3357384.3357814"},{"key":"4_CR4","doi-asserted-by":"crossref","unstructured":"Lin, Z., Wang, H., Mao, J., Zhao, W.X., Wang, C., Jiang, P., Wen, J.R.: Feature-aware diversified re-ranking with disentangled representations for relevant recommendation. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. pp. 3327\u20133335 (2022)","DOI":"10.1145\/3534678.3539130"},{"key":"4_CR5","doi-asserted-by":"crossref","unstructured":"Ma, J., Zhou, C., Yang, H., Cui, P., Wang, X., Zhu, W.: Disentangled self-supervision in sequential recommenders. In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. pp. 483\u2013491 (2020)","DOI":"10.1145\/3394486.3403091"},{"key":"4_CR6","unstructured":"Nwankpa, C., Ijomah, W., Gachagan, A., Marshall, S.: Activation functions: Comparison of trends in practice and research for deep learning. arXiv preprint arXiv:1811.03378 (2018)"},{"key":"4_CR7","doi-asserted-by":"crossref","unstructured":"Pi, Q., Zhou, G., Zhang, Y., Wang, Z., Ren, L., Fan, Y., Zhu, X., Gai, K.: Search-based user interest modeling with lifelong sequential behavior data for click-through rate prediction. In: Proceedings of the 29th ACM International Conference on Information & Knowledge Management. pp. 2685\u20132692 (2020)","DOI":"10.1145\/3340531.3412744"},{"key":"4_CR8","doi-asserted-by":"crossref","unstructured":"Qu, Y., Cai, H., Ren, K., Zhang, W., Yu, Y., Wen, Y., Wang, J.: Product-based neural networks for user response prediction. In: 2016 IEEE 16th International Conference on Data Mining (ICDM). pp. 1149\u20131154. IEEE (2016)","DOI":"10.1109\/ICDM.2016.0151"},{"key":"4_CR9","unstructured":"Rendle, S., Freudenthaler, C., Gantner, Z., Schmidt-Thieme, L.: Bpr: Bayesian personalized ranking from implicit feedback. arXiv preprint arXiv:1205.2618 (2012)"},{"key":"4_CR10","doi-asserted-by":"crossref","unstructured":"Rendle, S., Freudenthaler, C., Schmidt-Thieme, L.: Factorizing personalized markov chains for next-basket recommendation. In: Proceedings of the 19th international conference on World wide web. pp. 811\u2013820 (2010)","DOI":"10.1145\/1772690.1772773"},{"key":"4_CR11","doi-asserted-by":"crossref","unstructured":"Shen, Q., Tao, W., Zhang, J., Wen, H., Chen, Z., Lu, Q.: Sar-net: A scenario-aware ranking network for personalized fair recommendation in hundreds of travel scenarios. In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management. pp. 4094\u20134103 (2021)","DOI":"10.1145\/3459637.3481948"},{"key":"4_CR12","doi-asserted-by":"crossref","unstructured":"Shen, Q., Wen, H., Tao, W., Zhang, J., Lv, F., Chen, Z., Li, Z.: Deep interest highlight network for click-through rate prediction in trigger-induced recommendation. In: Proceedings of the ACM Web Conference 2022. pp. 422\u2013430 (2022)","DOI":"10.1145\/3485447.3511970"},{"key":"4_CR13","doi-asserted-by":"crossref","unstructured":"Sun, F., Liu, J., Wu, J., Pei, C., Lin, X., Ou, W., Jiang, P.: Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer. In: Proceedings of the 28th ACM international conference on information and knowledge management. pp. 1441\u20131450 (2019)","DOI":"10.1145\/3357384.3357895"},{"key":"4_CR14","doi-asserted-by":"crossref","unstructured":"Tang, J., Wang, K.: Personalized top-n sequential recommendation via convolutional sequence embedding. In: Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining. pp. 565\u2013573 (2018)","DOI":"10.1145\/3159652.3159656"},{"key":"4_CR15","doi-asserted-by":"crossref","unstructured":"Tao, W., Fu, Z.H., Li, L., Chen, Z., Wen, H., Liu, Y., Shen, Q., Chen, P.: A dual channel intent evolution network for predicting period-aware travel intentions at fliggy. In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management. pp. 3524\u20133533 (2022)","DOI":"10.1145\/3511808.3557135"},{"key":"4_CR16","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., Polosukhin, I.: Attention is all you need. Advances in neural information processing systems 30 (2017)"},{"key":"4_CR17","doi-asserted-by":"crossref","unstructured":"Wang, R., Fu, B., Fu, G., Wang, M.: Deep & cross network for ad click predictions. In: Proceedings of the ADKDD\u201917, pp.\u00a01\u20137 (2017)","DOI":"10.1145\/3124749.3124754"},{"key":"4_CR18","doi-asserted-by":"crossref","unstructured":"Wang, S., Hu, L., Wang, Y., Cao, L., Sheng, Q.Z., Orgun, M.: Sequential recommender systems: challenges, progress and prospects. arXiv preprint arXiv:2001.04830 (2019)","DOI":"10.24963\/ijcai.2019\/883"},{"key":"4_CR19","doi-asserted-by":"crossref","unstructured":"Wen, H., Zhang, J., Lin, Q., Yang, K., Huang, P.: Multi-level deep cascade trees for conversion rate prediction in recommendation system. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol.\u00a033, pp. 338\u2013345 (2019)","DOI":"10.1609\/aaai.v33i01.3301338"},{"key":"4_CR20","doi-asserted-by":"crossref","unstructured":"Wen, H., Zhang, J., Wang, Y., Lv, F., Bao, W., Lin, Q., Yang, K.: Entire space multi-task modeling via post-click behavior decomposition for conversion rate prediction. In: Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval. pp. 2377\u20132386 (2020)","DOI":"10.1145\/3397271.3401443"},{"key":"4_CR21","doi-asserted-by":"crossref","unstructured":"Xie, R., Wang, R., Zhang, S., Yang, Z., Xia, F., Lin, L.: Real-time relevant recommendation suggestion. In: Proceedings of the 14th ACM International Conference on Web Search and Data Mining. pp. 112\u2013120 (2021)","DOI":"10.1145\/3437963.3441733"},{"key":"4_CR22","doi-asserted-by":"crossref","unstructured":"Zhang, K., Qian, H., Cui, Q., Liu, Q., Li, L., Zhou, J., Ma, J., Chen, E.: Multi-interactive attention network for fine-grained feature learning in ctr prediction. In: Proceedings of the 14th ACM International Conference on Web Search and Data Mining. pp. 984\u2013992 (2021)","DOI":"10.1145\/3437963.3441761"},{"key":"4_CR23","doi-asserted-by":"crossref","unstructured":"Zhou, G., Mou, N., Fan, Y., Pi, Q., Bian, W., Zhou, C., Zhu, X., Gai, K.: Deep interest evolution network for click-through rate prediction. In: Proceedings of the AAAI Conference on Artificial Intelligence (2019)","DOI":"10.1609\/aaai.v33i01.33015941"},{"key":"4_CR24","doi-asserted-by":"crossref","unstructured":"Zhou, G., Zhu, X., Song, C., Fan, Y., Zhu, H., Ma, X., Yan, Y., Jin, J., Li, H., Gai, K.: Deep interest network for click-through rate prediction. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. pp. 1059\u20131068. ACM (2018)","DOI":"10.1145\/3219819.3219823"}],"container-title":["Lecture Notes in Computer Science","Advanced Data Mining and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-0850-8_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T05:03:19Z","timestamp":1734930199000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-0850-8_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,24]]},"ISBN":["9789819608492","9789819608508"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-0850-8_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,12,24]]},"assertion":[{"value":"24 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ADMA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Data Mining and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sydney, NSW","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","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":"3 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"adma2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/adma2024.github.io\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}