{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T01:16:43Z","timestamp":1765502203213,"version":"3.48.0"},"publisher-location":"New York, NY, USA","reference-count":26,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,10]]},"DOI":"10.1145\/3746252.3761509","type":"proceedings-article","created":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T01:03:42Z","timestamp":1762563822000},"page":"5923-5930","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["SMTIR: Scenario-Aware Multi-Trigger Induction Network for CTR Prediction"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4598-9505","authenticated-orcid":false,"given":"Xuan","family":"Ma","sequence":"first","affiliation":[{"name":"JD.com, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7731-8893","authenticated-orcid":false,"given":"Yu","family":"Shi","sequence":"additional","affiliation":[{"name":"JD.com, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5762-8497","authenticated-orcid":false,"given":"Hao","family":"Peng","sequence":"additional","affiliation":[{"name":"JD.com, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5960-922X","authenticated-orcid":false,"given":"Jia","family":"Duan","sequence":"additional","affiliation":[{"name":"JD.com, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8482-4091","authenticated-orcid":false,"given":"Zhanhao","family":"Ye","sequence":"additional","affiliation":[{"name":"JD.com, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5751-4924","authenticated-orcid":false,"given":"Kunyao","family":"Wang","sequence":"additional","affiliation":[{"name":"JD.com, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8250-8744","authenticated-orcid":false,"given":"Kai","family":"Yan","sequence":"additional","affiliation":[{"name":"JD.com, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7223-420X","authenticated-orcid":false,"given":"Long","family":"Chen","sequence":"additional","affiliation":[{"name":"JD.com, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4784-8095","authenticated-orcid":false,"given":"Zehua","family":"Zhang","sequence":"additional","affiliation":[{"name":"JD.com, Beijng, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2561-1919","authenticated-orcid":false,"given":"Changping","family":"Peng","sequence":"additional","affiliation":[{"name":"JD.com, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1379-5044","authenticated-orcid":false,"given":"Zhangang","family":"Lin","sequence":"additional","affiliation":[{"name":"JD.com, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-3275-2528","authenticated-orcid":false,"given":"Ching","family":"Law","sequence":"additional","affiliation":[{"name":"JD.com, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2025,11,10]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557082"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599922"},{"key":"e_1_3_2_1_3_1","unstructured":"Qiwei Chen Yue Xu Changhua Pei Shanshan Lv Tao Zhuang and Junfeng Ge. 2022. Efficient Long Sequential User Data Modeling for Click-Through Rate Prediction. arXiv:2209.12212 [cs.IR] https:\/\/arxiv.org\/abs\/2209.12212"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_1_5_1","volume-title":"POSO: Personalized Cold Start Modules for Large-scale Recommender Systems. CoRR","author":"Dai Shangfeng","year":"2021","unstructured":"Shangfeng Dai, Haobin Lin, Zhichen Zhao, Jianying Lin, Honghuan Wu, Zhe Wang, Sen Yang, and Ji Liu. 2021. POSO: Personalized Cold Start Modules for Large-scale Recommender Systems. CoRR, Vol. abs\/2108.04690 (2021). arXiv:2108.04690 https:\/\/arxiv.org\/abs\/2108.04690"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3463116"},{"key":"e_1_3_2_1_7_1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2015. Deep Residual Learning for Image Recognition. arXiv:1512.03385 [cs.CV] https:\/\/arxiv.org\/abs\/1512.03385"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3347043"},{"key":"e_1_3_2_1_9_1","volume-title":"Adam: A Method for Stochastic Optimization. Computer Science","author":"Kingma Diederik","year":"2014","unstructured":"Diederik Kingma and Jimmy Ba. 2014. Adam: A Method for Stochastic Optimization. Computer Science (2014)."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357814"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589335.3651486"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3627673.3680065"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330666"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412744"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3511970"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3481941"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3627673.3680030"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557336"},{"key":"e_1_3_2_1_19_1","volume-title":"Attention is all you need. Advances in neural information processing systems","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems, Vol. 30 (2017)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3124749.3124754"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543873.3584661"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3616855.3635829"},{"key":"e_1_3_2_1_23_1","volume-title":"DynInt: Dynamic Interaction Modeling for Large-scale Click-Through Rate Prediction. arXiv preprint arXiv:2301.08139","author":"Yan YaChen","year":"2023","unstructured":"YaChen Yan and Liubo Li. 2023. DynInt: Dynamic Interaction Modeling for Large-scale Click-Through Rate Prediction. arXiv preprint arXiv:2301.08139 (2023)."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015941"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219823"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098134"}],"event":{"name":"CIKM '25: The 34th ACM International Conference on Information and Knowledge Management","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"],"location":"Seoul Republic of Korea","acronym":"CIKM '25"},"container-title":["Proceedings of the 34th ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3746252.3761509","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T01:14:42Z","timestamp":1765502082000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3746252.3761509"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,10]]},"references-count":26,"alternative-id":["10.1145\/3746252.3761509","10.1145\/3746252"],"URL":"https:\/\/doi.org\/10.1145\/3746252.3761509","relation":{},"subject":[],"published":{"date-parts":[[2025,11,10]]},"assertion":[{"value":"2025-11-10","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}