{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T16:11:43Z","timestamp":1783786303287,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":31,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819228553","type":"print"},{"value":"9789819228560","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T00:00:00Z","timestamp":1783814400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T00:00:00Z","timestamp":1783814400000},"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\/978-981-92-2856-0_42","type":"book-chapter","created":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T15:15:21Z","timestamp":1783782921000},"page":"590-604","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["GA-LLMRec: Recommender Systems with\u00a0Graph-Augmented Large Language Models"],"prefix":"10.1007","author":[{"given":"Ding","family":"Luo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2216-8878","authenticated-orcid":false,"given":"Wenhui","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhengliang","family":"Ding","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Xiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zheng","family":"Dong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guojun","family":"Dai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,12]]},"reference":[{"key":"42_CR1","doi-asserted-by":"publisher","first-page":"128718","DOI":"10.1016\/j.neucom.2024.128718","volume":"617","author":"MF Aljunid","year":"2025","unstructured":"Aljunid, M.F., Manjaiah, D., Hooshmand, M.K., Ali, W.A., Shetty, A.M., Alzoubah, S.Q.: A collaborative filtering recommender systems: survey. Neurocomputing 617, 128718 (2025)","journal-title":"Neurocomputing"},{"key":"42_CR2","doi-asserted-by":"crossref","unstructured":"Areeb, Q.M., et al.: Filter bubbles in recommender systems: fact or fallacy\u2013a systematic review. WIREs Data Min. Knowl. Discovery 13(6), e1512 (2023)","DOI":"10.1002\/widm.1512"},{"key":"42_CR3","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: 17th ACM Conference on Recommender Systems, pp. 1007\u20131014 (2023)","DOI":"10.1145\/3604915.3608857"},{"key":"42_CR4","doi-asserted-by":"crossref","unstructured":"Chen, Z., Gan, W., Wu, J., Hu, K., Lin, H.: Data scarcity in recommendation systems: a survey. ACM Trans. Recommender Syst. (2024)","DOI":"10.1145\/3639063"},{"key":"42_CR5","first-page":"111169","volume":"283","author":"D Ge","year":"2024","unstructured":"Ge, D., Dong, Z., Cheng, Y., Wu, Y.: An enhanced spatio-temporal constraints network for anomaly detection in multivariate time series. KBS 283, 111169 (2024)","journal-title":"KBS"},{"key":"42_CR6","doi-asserted-by":"crossref","unstructured":"He, X., Deng, K., Wang, X., Li, Y., Zhang, Y., Wang, M.: LightGCN: simplifying and powering graph convolution network for recommendation. In: 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 639\u2013648 (2020)","DOI":"10.1145\/3397271.3401063"},{"key":"42_CR7","doi-asserted-by":"crossref","unstructured":"He, X., Liao, L., Zhang, H., Nie, L., Hu, X., Chua, T.S.: Neural collaborative filtering. In: WWW, pp. 173\u2013182 (2017)","DOI":"10.1145\/3038912.3052569"},{"key":"42_CR8","unstructured":"Hidasi, B.: Session-based recommendations with recurrent neural networks. arXiv preprint arXiv:1511.06939 (2015)"},{"key":"42_CR9","unstructured":"Hu, E.J., et al.: LoRA: low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685 (2021)"},{"key":"42_CR10","unstructured":"Jiang, C., et al.: Beyond utility: evaluating LLM as recommender. arXiv preprint arXiv:2411.00331 (2024)"},{"key":"42_CR11","doi-asserted-by":"crossref","unstructured":"Jiang, M., et al.: Item-side fairness of large language model-based recommendation system. In: WWWW, pp. 4717\u20134726 (2024)","DOI":"10.1145\/3589334.3648158"},{"key":"42_CR12","doi-asserted-by":"crossref","unstructured":"Kang, W.C., McAuley, J.: Self-attentive sequential recommendation. In: IEEE international conference on data mining (ICDM), pp. 197\u2013206. IEEE (2018)","DOI":"10.1109\/ICDM.2018.00035"},{"issue":"3","key":"42_CR13","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1177\/0267323117695734","volume":"32","author":"R Karlsen","year":"2017","unstructured":"Karlsen, R., Steen-Johnsen, K., Wolleb\u00e6k, D., Enjolras, B.: Echo chamber and trench warfare dynamics in online debates. Eur. J. Commun. 32(3), 257\u2013273 (2017)","journal-title":"Eur. J. Commun."},{"key":"42_CR14","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"42_CR15","unstructured":"Lazovich, T.: Filter bubbles and affective polarization in user-personalized large language model outputs. In: NeurIPS, pp.\u00a01\u20139 (2023)"},{"key":"42_CR16","unstructured":"Shen, D., Qin, C., Wang, C., Dong, Z., Zhu, H., Xiong, H.: Topic modeling revisited: a document graph-based neural network perspective. In: NeurIPS, vol. 34, pp. 14681\u201314693 (2021)"},{"key":"42_CR17","doi-asserted-by":"crossref","unstructured":"Sun, F., et al.: BERT4Rec: sequential recommendation with bidirectional encoder representations from transformer. In: 28th ACM International Conference on Information and Knowledge Management, pp. 1441\u20131450 (2019)","DOI":"10.1145\/3357384.3357895"},{"key":"42_CR18","doi-asserted-by":"crossref","unstructured":"Sun, J., et al.: Neighbor interaction aware graph convolution networks for recommendation. In: 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1289\u20131298 (2020)","DOI":"10.1145\/3397271.3401123"},{"key":"42_CR19","doi-asserted-by":"crossref","unstructured":"Tang, J., Wang, K.: Personalized top-n sequential recommendation via convolutional sequence embedding. In: 11th ACM International Conference on Web Search and Data Mining, pp. 565\u2013573 (2018)","DOI":"10.1145\/3159652.3159656"},{"key":"42_CR20","doi-asserted-by":"crossref","unstructured":"Wang, X., He, X., Wang, M., Feng, F., Chua, T.S.: Neural graph collaborative filtering. In: 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 165\u2013174 (2019)","DOI":"10.1145\/3331184.3331267"},{"key":"42_CR21","doi-asserted-by":"crossref","unstructured":"Wang, X., Wu, L., Hong, L., Liu, H., Fu, Y.: LLM-enhanced user-item interactions: leveraging edge information for optimized recommendations. arXiv preprint arXiv:2402.09617 (2024)","DOI":"10.1145\/3757925"},{"issue":"5","key":"42_CR22","first-page":"60","volume":"27","author":"L Wu","year":"2024","unstructured":"Wu, L., Zheng, Z., Qiu, Z., Wang, H., Gu, H., Shen, T., Qin, C., Zhu, C., Zhu, H., Liu, Q., et al.: A survey on large language models for recommendation. WWW 27(5), 60 (2024)","journal-title":"WWW"},{"key":"42_CR23","doi-asserted-by":"crossref","unstructured":"Yang, L., et al.: DGRec: graph neural network for recommendation with diversified embedding generation. In: ACM WSDM Conference (2023)","DOI":"10.1145\/3539597.3570472"},{"issue":"2","key":"42_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3597022","volume":"42","author":"Y Yang","year":"2023","unstructured":"Yang, Y., Zhang, C., Song, X., Dong, Z., Zhu, H., Li, W.: Contextualized knowledge graph embedding for explainable talent training course recommendation. ACM Trans. Inf. Syst. 42(2), 1\u201327 (2023)","journal-title":"ACM Trans. Inf. Syst."},{"issue":"4","key":"42_CR25","first-page":"4047","volume":"35","author":"Y Ye","year":"2022","unstructured":"Ye, Y., et al.: MANE: organizational network embedding with multiplex attentive neural networks. TKDE 35(4), 4047\u20134061 (2022)","journal-title":"TKDE"},{"key":"42_CR26","doi-asserted-by":"crossref","unstructured":"Ying, R., He, R., Chen, K., Eksombatchai, P., Hamilton, W.L., Leskovec, J.: Graph convolutional neural networks for web-scale recommender systems. In: SIGKDD, pp. 974\u2013983 (2018)","DOI":"10.1145\/3219819.3219890"},{"key":"42_CR27","doi-asserted-by":"crossref","unstructured":"Yu, C., Zhao, J., Wu, X., Luo, Y., Xiao, Y.: TPGRec: text-enhanced and popularity-smoothing graph collaborative filtering for long-tail item recommendation. Neurocomputing 129539 (2025)","DOI":"10.1016\/j.neucom.2025.129539"},{"key":"42_CR28","doi-asserted-by":"crossref","unstructured":"Yu, Y., et al.: Large language model as attributed training data generator: a tale of diversity and bias. In: NeurIPS, pp. 55734\u201355784 (2023)","DOI":"10.52202\/075280-2433"},{"key":"42_CR29","doi-asserted-by":"crossref","unstructured":"Zhang, J., Bao, K., Zhang, Y., Wang, W., Feng, F., He, X.: Is ChatGPT fair for recommendation? Evaluating fairness in large language model recommendation. In: RecSys, pp. 993\u2013999 (2023)","DOI":"10.1145\/3604915.3608860"},{"key":"42_CR30","doi-asserted-by":"crossref","unstructured":"Zheng, D., Liu, J., Li, R.H., Aslay, C., Chen, Y.C., Huang, X.: Querying intimate-core groups in weighted graphs. In: ICSC, pp. 156\u2013163. IEEE (2017)","DOI":"10.1109\/ICSC.2017.80"},{"key":"42_CR31","doi-asserted-by":"crossref","unstructured":"Zheng, Z., Chao, W., Qiu, Z., Zhu, H., Xiong, H.: Harnessing large language models for text-rich sequential recommendation. In: WWW, pp. 3207\u20133216 (2024)","DOI":"10.1145\/3589334.3645358"}],"container-title":["Lecture Notes in Computer Science","Knowledge Science, Engineering and Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-2856-0_42","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T15:15:24Z","timestamp":1783782924000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-2856-0_42"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,12]]},"ISBN":["9789819228553","9789819228560"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-2856-0_42","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,12]]},"assertion":[{"value":"12 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"KSEM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Knowledge Science, Engineering and Management","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Beijing","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":"17 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ksem2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ksem2026.rosc.org.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}