{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T20:18:18Z","timestamp":1783023498152,"version":"3.54.6"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819219254","type":"print"},{"value":"9789819219261","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T00:00:00Z","timestamp":1782777600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T00:00:00Z","timestamp":1782777600000},"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":[[2027]]},"DOI":"10.1007\/978-981-92-1926-1_19","type":"book-chapter","created":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T15:32:47Z","timestamp":1782747167000},"page":"227-238","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SIMC: LLM-Driven Generative Recommendation with\u00a0Semantic Item Modeling and\u00a0Constraints"],"prefix":"10.1007","author":[{"given":"Minghao","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiale","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,30]]},"reference":[{"key":"19_CR1","unstructured":"Achiam, J., et al.: GPT-4 technical report. arXiv preprint arXiv:2303.08774 (2023)"},{"key":"19_CR2","doi-asserted-by":"crossref","unstructured":"Bao, K., Zhang, J., Zhang, Y., Wang, W., Feng, F., He, X.: Tallrec: an effective and efficient tuning framework to align large language model with recommendation. In: Proceedings of the 17th ACM Conference on Recommender Systems, pp. 1007\u20131014 (2023)","DOI":"10.1145\/3604915.3608857"},{"key":"19_CR3","unstructured":"Cui, Z., Ma, J., Zhou, C., Zhou, J., Yang, H.: M6-rec: generative pretrained language models are open-ended recommender systems. arXiv preprint arXiv:2205.08084 (2022)"},{"key":"19_CR4","doi-asserted-by":"crossref","unstructured":"Deldjoo, Y., et al.: A review of modern recommender systems using generative models (gen-recsys). In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 6448\u20136458 (2024)","DOI":"10.1145\/3637528.3671474"},{"key":"19_CR5","doi-asserted-by":"crossref","unstructured":"Geng, S., Liu, S., Fu, Z., Ge, Y., Zhang, Y.: Recommendation as language processing (RLP): a unified pretrain, personalized prompt & predict paradigm (p5). In: Proceedings of the 16th ACM Conference on Recommender Systems, pp. 299\u2013315 (2022)","DOI":"10.1145\/3523227.3546767"},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"He, R., McAuley, J.: Ups and downs: modeling the visual evolution of fashion trends with one-class collaborative filtering. In: Proceedings of the 25th International Conference on World Wide Web, pp. 507\u2013517 (2016)","DOI":"10.1145\/2872427.2883037"},{"key":"19_CR7","unstructured":"Hidasi, B.: Session-based recommendations with recurrent neural networks. arXiv preprint arXiv:1511.06939 (2015)"},{"key":"19_CR8","doi-asserted-by":"crossref","unstructured":"Hua, W., Xu, S., Ge, Y., Zhang, Y.: How to index item ids for recommendation foundation models. In: Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, pp. 195\u2013204 (2023)","DOI":"10.1145\/3624918.3625339"},{"key":"19_CR9","doi-asserted-by":"crossref","unstructured":"Kang, W.C., McAuley, J.: Self-attentive sequential recommendation. In: 2018 IEEE International Conference on Data Mining (ICDM), pp. 197\u2013206. IEEE (2018)","DOI":"10.1109\/ICDM.2018.00035"},{"key":"19_CR10","doi-asserted-by":"crossref","unstructured":"Liao, J., et al.: Llara: large language-recommendation assistant. In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1785\u20131795 (2024)","DOI":"10.1145\/3626772.3657690"},{"key":"19_CR11","doi-asserted-by":"crossref","unstructured":"Ma, C., Kang, P., Liu, X.: Hierarchical gating networks for sequential recommendation. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 825\u2013833 (2019)","DOI":"10.1145\/3292500.3330984"},{"key":"19_CR12","doi-asserted-by":"crossref","unstructured":"McAuley, J., Targett, C., Shi, Q., Van Den\u00a0Hengel, A.: Image-based recommendations on styles and substitutes. In: Proceedings of the 38th international ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 43\u201352 (2015)","DOI":"10.1145\/2766462.2767755"},{"key":"19_CR13","doi-asserted-by":"crossref","unstructured":"Rajput, S., et al.: Recommender systems with generative retrieval. In: Advances in Neural Information Processing Systems, vol. 36, pp. 10299\u201310315 (2023)","DOI":"10.52202\/075280-0452"},{"key":"19_CR14","doi-asserted-by":"crossref","unstructured":"Ren, X., et al.: Representation learning with large language models for recommendation. In: Proceedings of the ACM on Web Conference 2024, pp. 3464\u20133475 (2024)","DOI":"10.1145\/3589334.3645458"},{"key":"19_CR15","doi-asserted-by":"crossref","unstructured":"Sun, F., et al.: 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":"19_CR16","doi-asserted-by":"crossref","unstructured":"Tan, J., Xu, S., Hua, W., Ge, Y., Li, Z., Zhang, Y.: IDGenRec: LLM-RecSys alignment with textual id learning. In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 355\u2013364 (2024)","DOI":"10.1145\/3626772.3657821"},{"key":"19_CR17","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":"19_CR18","unstructured":"Touvron, H., et al.: Llama: open and efficient foundation language models. arXiv preprint arXiv:2302.13971 (2023)"},{"issue":"5","key":"19_CR19","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1007\/s11280-024-01291-2","volume":"27","author":"L Wu","year":"2024","unstructured":"Wu, L., et al.: A survey on large language models for recommendation. World Wide Web 27(5), 60 (2024)","journal-title":"World Wide Web"},{"key":"19_CR20","unstructured":"Yang, A., et al.: Qwen2. 5 technical report. arXiv preprint arXiv:2412.15115 (2024)"},{"key":"19_CR21","doi-asserted-by":"crossref","unstructured":"Zhang, C., et al.: Spar: personalized content-based recommendation via long engagement attention. arXiv preprint arXiv:2402.10555 (2024)","DOI":"10.2139\/ssrn.5167460"},{"key":"19_CR22","unstructured":"Zhang, J., Xie, R., Hou, Y., Zhao, X., Lin, L., Wen, J.R.: Recommendation as instruction following: a large language model empowered recommendation approach. ACM Trans. Inf. Syst. (2023)"},{"key":"19_CR23","doi-asserted-by":"crossref","unstructured":"Zhang, T., et\u00a0al.: Feature-level deeper self-attention network for sequential recommendation. In: IJCAI, pp. 4320\u20134326 (2019)","DOI":"10.24963\/ijcai.2019\/600"},{"key":"19_CR24","doi-asserted-by":"crossref","unstructured":"Zhao, Z., et\u00a0al.: Recommender systems in the era of large language models (LLMs). IEEE Trans. Knowl. Data Eng. (2024)","DOI":"10.1109\/TKDE.2024.3392335"},{"key":"19_CR25","doi-asserted-by":"crossref","unstructured":"Zhou, K., et al.: S3-rec: self-supervised learning for sequential recommendation with mutual information maximization. In: Proceedings of the 29th ACM International Conference on Information & Knowledge Management, pp. 1893\u20131902 (2020)","DOI":"10.1145\/3340531.3411954"}],"container-title":["Lecture Notes in Computer Science","Data Science: Foundations and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-1926-1_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T19:34:55Z","timestamp":1783020895000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-1926-1_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,30]]},"ISBN":["9789819219254","9789819219261"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-1926-1_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,30]]},"assertion":[{"value":"30 June 2026","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":"Hong Kong","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":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 June 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 June 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.pakdd2026.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}