{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T00:55:40Z","timestamp":1772931340003,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":21,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,13]]},"DOI":"10.1145\/3589335.3651558","type":"proceedings-article","created":{"date-parts":[[2024,5,12]],"date-time":"2024-05-12T18:41:21Z","timestamp":1715539281000},"page":"919-922","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Discrete Semantic Tokenization for Deep CTR Prediction"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6087-383X","authenticated-orcid":false,"given":"Qijiong","family":"Liu","sequence":"first","affiliation":[{"name":"PolyU, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7847-0641","authenticated-orcid":false,"given":"Hengchang","family":"Hu","sequence":"additional","affiliation":[{"name":"National University of Singapore, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4085-5295","authenticated-orcid":false,"given":"Jiahao","family":"Wu","sequence":"additional","affiliation":[{"name":"PolyU, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5666-8320","authenticated-orcid":false,"given":"Jieming","family":"Zhu","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8507-3716","authenticated-orcid":false,"given":"Min-Yen","family":"Kan","sequence":"additional","affiliation":[{"name":"National University of Singapore, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3130-0554","authenticated-orcid":false,"given":"Xiao-Ming","family":"Wu","sequence":"additional","affiliation":[{"name":"PolyU, Hong Kong, Hong Kong"}]}],"member":"320","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Neural machine translation by jointly learning to align and translate. arXiv","author":"Bahdanau Dzmitry","year":"2014","unstructured":"Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. arXiv (2014)."},{"key":"e_1_3_2_2_2_1","volume-title":"1st DLP4Rec. 1--4.","author":"Chen Qiwei","unstructured":"Qiwei Chen, Huan Zhao, Wei Li, Pipei Huang, and Wenwu Ou. 2019. Behavior sequence transformer for e-commerce recommendation in alibaba. In 1st DLP4Rec. 1--4."},{"key":"e_1_3_2_2_3_1","volume-title":"An introduction to ROC analysis. PRL","author":"Fawcett Tom","year":"2006","unstructured":"Tom Fawcett. 2006. An introduction to ROC analysis. PRL (2006)."},{"key":"e_1_3_2_2_4_1","unstructured":"Huifeng Guo Ruiming Tang Yunming Ye Zhenguo Li and Xiuqiang He. 2017. DeepFM: a factorization-machine based neural network for CTR prediction. arXiv (2017)."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/582415.582418"},{"key":"e_1_3_2_2_6_1","unstructured":"Bowen Jin Hansi Zeng Guoyin Wang Xiusi Chen Tianxin Wei Ruirui Li Zhengyang Wang Zheng Li Yang Li Hanqing Lu et al. 2023. Language Models As Semantic Indexers. arXiv (2023)."},{"key":"e_1_3_2_2_7_1","volume-title":"Adam: A Method for Stochastic Optimization. ICLR","author":"Kingma Diederik P","year":"2015","unstructured":"Diederik P Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. ICLR (2015)."},{"key":"e_1_3_2_2_8_1","unstructured":"Qijiong Liu Jieming Zhu Quanyu Dai and Xiaoming Wu. 2022. Boosting Deep CTR Prediction with a Plug-and-Play Pre-trainer for News Recommendation. In COLING. International Committee on Computational Linguistics."},{"key":"e_1_3_2_2_9_1","unstructured":"Qijiong Liu Jieming Zhu Quanyu Dai and Xiao-Ming Wu. 2023. Only Encode Once: Making Content-based News Recommender Greener."},{"key":"e_1_3_2_2_10_1","unstructured":"Kelong Mao Jieming Zhu Liangcai Su Guohao Cai Yuru Li and Zhenhua Dong. 2023. FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction. In AAAI."},{"key":"e_1_3_2_2_11_1","unstructured":"Shashank Rajput Nikhil Mehta Anima Singh Raghunandan H Keshavan Trung Vu Lukasz Heldt Lichan Hong Yi Tay Vinh Q Tran Jonah Samost et al. 2023. Recommender Systems with Generative Retrieval. arXiv (2023)."},{"key":"e_1_3_2_2_12_1","volume-title":"NIPS","volume":"30","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. NIPS, Vol. 30 (2017)."},{"key":"e_1_3_2_2_13_1","volume-title":"ADKDD (Halifax, NS, Canada) (ADKDD'17). ACM","author":"Wang Ruoxi","unstructured":"Ruoxi Wang, Bin Fu, Gang Fu, and Mingliang Wang. 2017. Deep & Cross Network for Ad Click Predictions. In ADKDD (Halifax, NS, Canada) (ADKDD'17). ACM, New York, NY, USA, Article 12, 7 pages."},{"key":"e_1_3_2_2_14_1","unstructured":"Chuhan Wu Fangzhao Wu Suyu Ge Tao Qi Yongfeng Huang and Xing Xie. 2019. Neural News Recommendation with Multi-head Self-attention. In EMNLP-IJCNLP."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"crossref","unstructured":"Chuhan Wu Fangzhao Wu Tao Qi and Yongfeng Huang. 2022. UserBERT: Pre-training User Model with Contrastive Self-supervision. In SIGIR. 2087--2092.","DOI":"10.1145\/3477495.3531810"},{"key":"e_1_3_2_2_16_1","volume-title":"NewsBERT: Distilling pre-trained language model for intelligent news application. arXiv","author":"Wu Chuhan","year":"2021","unstructured":"Chuhan Wu, Fangzhao Wu, Yang Yu, Tao Qi, Yongfeng Huang, and Qi Liu. 2021. NewsBERT: Distilling pre-trained language model for intelligent news application. arXiv (2021)."},{"key":"e_1_3_2_2_17_1","volume-title":"Mind: A large-scale dataset for news recommendation. In ACL. 3597--3606.","author":"Wu Fangzhao","year":"2020","unstructured":"Fangzhao Wu, Ying Qiao, Jiun-Hung Chen, Chuhan Wu, Tao Qi, Jianxun Lian, Danyang Liu, Xing Xie, Jianfeng Gao, Winnie Wu, et al. 2020. Mind: A large-scale dataset for news recommendation. In ACL. 3597--3606."},{"key":"e_1_3_2_2_18_1","volume-title":"Where to go next for recommender systems? id-vs. modality-based recommender models revisited. arXiv","author":"Yuan Zheng","year":"2023","unstructured":"Zheng Yuan, Fajie Yuan, Yu Song, Youhua Li, Junchen Fu, Fei Yang, Yunzhu Pan, and Yongxin Ni. 2023. Where to go next for recommender systems? id-vs. modality-based recommender models revisited. arXiv (2023)."},{"key":"e_1_3_2_2_19_1","volume-title":"TASLP","volume":"30","author":"Zeghidour Neil","year":"2021","unstructured":"Neil Zeghidour, Alejandro Luebs, Ahmed Omran, Jan Skoglund, and Marco Tagliasacchi. 2021. Soundstream: An end-to-end neural audio codec. TASLP, Vol. 30 (2021)."},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"crossref","unstructured":"Guorui Zhou Xiaoqiang Zhu Chenru Song Ying Fan Han Zhu Xiao Ma Yanghui Yan Junqi Jin Han Li and Kun Gai. 2018. Deep interest network for click-through rate prediction. In SIGKDD. 1059--1068.","DOI":"10.1145\/3219819.3219823"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"crossref","unstructured":"Jieming Zhu Jinyang Liu Shuai Yang Qi Zhang and Xiuqiang He. 2021. Open Benchmarking for Click-Through Rate Prediction. In CIKM. 2759--2769.","DOI":"10.1145\/3459637.3482486"}],"event":{"name":"WWW '24: The ACM Web Conference 2024","location":"Singapore Singapore","acronym":"WWW '24","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Companion Proceedings of the ACM Web Conference 2024"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589335.3651558","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3589335.3651558","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:35:48Z","timestamp":1755822948000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589335.3651558"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":21,"alternative-id":["10.1145\/3589335.3651558","10.1145\/3589335"],"URL":"https:\/\/doi.org\/10.1145\/3589335.3651558","relation":{},"subject":[],"published":{"date-parts":[[2024,5,13]]},"assertion":[{"value":"2024-05-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}