{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:25:33Z","timestamp":1760059533547,"version":"build-2065373602"},"reference-count":61,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"11","license":[{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62432002","62406061","T2293773"],"award-info":[{"award-number":["62432002","62406061","T2293773"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2023QF159"],"award-info":[{"award-number":["ZR2023QF159"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"name":"CCF-DiDi GAIA Collaborative Research Funds","award":["CCF-DiDi GAIA 202504"],"award-info":[{"award-number":["CCF-DiDi GAIA 202504"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1109\/tkde.2025.3605824","type":"journal-article","created":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T17:54:47Z","timestamp":1756922087000},"page":"6582-6596","source":"Crossref","is-referenced-by-count":0,"title":["Personalized Review Summarization by Using Graph-Based Retrieval Augmemted Generation"],"prefix":"10.1109","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1117-2890","authenticated-orcid":false,"given":"Shuo","family":"Shang","sequence":"first","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1033-6598","authenticated-orcid":false,"given":"Xin","family":"Cheng","sequence":"additional","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8729-858X","authenticated-orcid":false,"given":"Yiren","family":"Xiong","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-1319-431X","authenticated-orcid":false,"given":"Feng","family":"Guo","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1301-3700","authenticated-orcid":false,"given":"Shen","family":"Gao","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiuying","family":"Chen","sequence":"additional","affiliation":[{"name":"King Abdullah University of Science and Technology, Thuwal, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Wang","sequence":"additional","affiliation":[{"name":"Ant Group, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongbo","family":"Wang","sequence":"additional","affiliation":[{"name":"Ant Group, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongyan","family":"Zhao","sequence":"additional","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9201-7776","authenticated-orcid":false,"given":"Rui","family":"Yan","sequence":"additional","affiliation":[{"name":"Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33016690"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.528"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462854"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3358161"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/591"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401039"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1525\/9780520940420-020"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"article-title":"RoBERTa: A robustly optimized BERT pretraining approach","year":"2019","author":"Liu","key":"ref9"},{"year":"2023","key":"ref10","article-title":"Introducing chatgpt"},{"year":"2023","key":"ref11","article-title":"GPT-4 technical report"},{"article-title":"LLaMA: Open and efficient foundation language models","year":"2023","author":"Touvron","key":"ref12"},{"article-title":"OPT-IML: Scaling language model instruction meta learning through the lens of generalization","year":"2023","author":"Iyer","key":"ref13"},{"year":"2023","key":"ref14","article-title":"Introducing claude"},{"article-title":"GLM-130B: An open bilingual pre-trained model","year":"2022","author":"Zeng","key":"ref15"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/1014052.1014073"},{"key":"ref17","first-page":"1985","article-title":"Empirical analysis of exploiting review helpfulness for extractive summarization of online reviews","volume-title":"Proc. COLING 25th Int. Conf. Comput. Linguistics: Tech. Papers","author":"Xiong"},{"key":"ref18","first-page":"9459","article-title":"Retrieval-augmented generation for knowledge-intensive NLP tasks","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Lewis"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.550"},{"article-title":"Contrastive retrieval-augmented generation","year":"2024","author":"Sun","key":"ref20"},{"journal-title":"Trans. Mach. Learn. Res.","article-title":"E2E-rag: End-to-end retrieval-augmented generation with joint optimization","author":"Xie","key":"ref21"},{"key":"ref22","first-page":"2206","article-title":"Improving language models by retrieving from trillions of tokens","volume-title":"Proc. Conf. Mach. Learn.","author":"Borgeaud","year":"2022"},{"article-title":"Ragas: An evaluation framework for retrieval-augmented generation","year":"2023","author":"Mallen","key":"ref23"},{"article-title":"Towards personalized review summarization by modeling historical reviews from customer and product separately","year":"2023","author":"Cheng","key":"ref24"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-industry.3"},{"article-title":"Tinyrag: Efficient and private rag on consumer devices","year":"2024","author":"Yu","key":"ref26"},{"article-title":"Literag: Lightweight retrieval-augmented generation for local deployment","year":"2024","author":"Chen","key":"ref27"},{"key":"ref28","first-page":"5998","article-title":"Attention is all you need","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Vaswani"},{"article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kipf","key":"ref29"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/540"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N19-1240"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.552"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.5555\/3524938.3525087"},{"key":"ref35","first-page":"9912","article-title":"Unsupervised learning of visual features by contrasting cluster assignments","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Caron"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i10.17037"},{"key":"ref37","article-title":"Contrastive representation distillation","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Tian","year":"2020"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01603"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.naacl-main.427"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.393"},{"key":"ref42","first-page":"19580","article-title":"Directed graph contrastive learning","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Tong"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.482"},{"key":"ref44","first-page":"10890","article-title":"R-drop: Regularized dropout for neural networks","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Liang"},{"key":"ref45","article-title":"Contrastive learning with adversarial perturbations for conditional text generation","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Lee","year":"2021"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.72"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.491"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/p17-1099"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/d18-1443"},{"article-title":"ChunkRAG: Novel LLM-chunk filtering method for RAG systems","year":"2024","author":"Singh","key":"ref50"},{"article-title":"LightRAG: Simple and fast retrieval-augmented generation","year":"2024","author":"Guo","key":"ref51"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/2766462.2767755"},{"key":"ref53","first-page":"74","article-title":"ROUGE: A package for automatic evaluation of summaries","volume-title":"Proc. Text Summarization Branches Out","author":"Lin"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-30586-6_38"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2010.764"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/644"},{"key":"ref57","article-title":"Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms","volume-title":"Worked Examples, and Case Studies. Cambridge","author":"Kelleher","year":"2015"},{"key":"ref58","first-page":"8026","article-title":"PyTorch: An imperative style, high-performance deep learning library","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Paszke"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-demos.6"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.neuro.26.041002.131047"},{"article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","year":"2014","author":"Chung","key":"ref61"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/69\/11197180\/11150539.pdf?arnumber=11150539","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:55:33Z","timestamp":1760032533000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11150539\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11]]},"references-count":61,"journal-issue":{"issue":"11"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2025.3605824","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"type":"print","value":"1041-4347"},{"type":"electronic","value":"1558-2191"},{"type":"electronic","value":"2326-3865"}],"subject":[],"published":{"date-parts":[[2025,11]]}}}