{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T15:35:59Z","timestamp":1775230559575,"version":"3.50.1"},"reference-count":39,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,7,5]],"date-time":"2024-07-05T00:00:00Z","timestamp":1720137600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,7,5]],"date-time":"2024-07-05T00:00:00Z","timestamp":1720137600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100009625","name":"Beijing Social Science Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100009625","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015749","name":"Communication University of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100015749","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,5]]},"DOI":"10.1109\/snpd61259.2024.10673956","type":"proceedings-article","created":{"date-parts":[[2024,9,17]],"date-time":"2024-09-17T18:47:50Z","timestamp":1726598870000},"page":"81-86","source":"Crossref","is-referenced-by-count":3,"title":["A Review of Methods Using Large Language Models in News Recommendation Systems"],"prefix":"10.1109","author":[{"given":"Xinmiao","family":"Li","sequence":"first","affiliation":[{"name":"University of China,School of Computer and Cyber Sciences Communication,Beijing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuang","family":"Feng","sequence":"additional","affiliation":[{"name":"University of China,School of Computer and Cyber Sciences Communication,Beijing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of China,School of Computer and Cyber Sciences Communication,Beijing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-72079-9_10"},{"key":"ref2","first-page":"73","article-title":"Content-based Recommender Systems: State of the Art and Trends","author":"Lops","year":"2010","journal-title":"Recommender Systems Handbook"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/963770.963772"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015394"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1023\/A:1006544522159"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1023\/A:1021240730564"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3523227.3546767"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.3389\/fdata.2021.602071"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00619"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-024-01291-2"},{"key":"ref12","article-title":"Determlr: Augmenting llm-based logical reasoning from indeterminacy to determinacy","author":"Sun","year":"2023","journal-title":"arXiv preprint arXiv:2305.15301"},{"key":"ref13","article-title":"A survey of large language models","author":"Zhao","year":"2023","journal-title":"arXiv preprint arXiv:2303.18223"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3610646"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3608829"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-naacl.39"},{"key":"ref17","article-title":"Zero-shot next-item recommendation using large pre-trained language models","author":"Wang","year":"2023","journal-title":"arXiv preprint arXiv:2304.03153"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-56060-6_24"},{"key":"ref19","article-title":"Recommendation as instruction following: A large language model empowered recommendation approach","author":"Zhang","year":"2023","journal-title":"arXiv preprint arXiv:2305.07001"},{"key":"ref20","article-title":"Gpt4rec: A generative framework for personalized recommendation and user interests interpretation","author":"Li","year":"2023","journal-title":"arXiv preprint arXiv:2304.03879"},{"key":"ref21","article-title":"Generative sequential recommendation with gptrec","author":"Petrov","year":"2023","journal-title":"arXiv preprint arXiv:2306.11114"},{"key":"ref22","article-title":"Language models are realistic tabular data generators","author":"Borisov","year":"2022","journal-title":"arXiv preprint arXiv:2210.06280"},{"key":"ref23","article-title":"Improving code example recommendations on informal documentation using bert and query-aware lsh: A comparative study","author":"Rahmani","year":"2023","journal-title":"arXiv preprint arXiv:2305.03017"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583434"},{"key":"ref25","article-title":"Generate natural language explanations for recommendation","author":"Chen","year":"2021","journal-title":"arXiv preprint arXiv:2101.03392"},{"key":"ref26","article-title":"A preliminary study of chatgpt on news recommendation: Personalization, provider fairness, fake news","author":"Li","year":"2023","journal-title":"arXiv preprint arXiv:2306.10702"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/BigData47090.2019.9005459"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186175"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1671"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3463069"},{"key":"ref31","article-title":"A first look at llm-powered generative news recommendation","author":"Liu","year":"2023","journal-title":"arXiv preprint arXiv:2305.06566"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2024.049129"},{"key":"ref33","article-title":"News recommendation with category description by a large language model","author":"Yada","year":"2024"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3589334.3645448"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3589334.3645358"},{"key":"ref36","doi-asserted-by":"crossref","DOI":"10.1145\/3616855.3635845","article-title":"Once: Boosting content-based recommendation with both open-and closed-source large language models","volume-title":"Proc. 2023 Web Search and Data Mining","author":"Liu"},{"key":"ref37","article-title":"Pbnr: Prompt-based news recommender system","author":"Li","year":"2023","journal-title":"arXiv preprint arXiv:2304.07862"},{"key":"ref38","article-title":"Recprompt: A prompt tuning framework for news recommendation using large language models","author":"Liu","year":"2023","journal-title":"arXiv preprint arXiv:2312.10463"},{"key":"ref39","article-title":"Exploring fine-tuning chatgpt for news recommendation","author":"Li","year":"2023","journal-title":"arXiv preprint arXiv:2311.05850"}],"event":{"name":"2024 IEEE\/ACIS 27th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel\/Distributed Computing (SNPD)","location":"Beijing, China","start":{"date-parts":[[2024,7,5]]},"end":{"date-parts":[[2024,7,7]]}},"container-title":["2024 IEEE\/ACIS 27th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel\/Distributed Computing (SNPD)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10673894\/10673903\/10673956.pdf?arnumber=10673956","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T06:05:52Z","timestamp":1726812352000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10673956\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,5]]},"references-count":39,"URL":"https:\/\/doi.org\/10.1109\/snpd61259.2024.10673956","relation":{},"subject":[],"published":{"date-parts":[[2024,7,5]]}}}