{"id":"https://openalex.org/W4403582436","doi":"https://doi.org/10.1145/3627673.3679987","title":"RecPrompt: A Self-tuning Prompting Framework for News Recommendation Using Large Language Models","display_name":"RecPrompt: A Self-tuning Prompting Framework for News Recommendation Using Large Language Models","publication_year":2024,"publication_date":"2024-10-20","ids":{"openalex":"https://openalex.org/W4403582436","doi":"https://doi.org/10.1145/3627673.3679987"},"language":"en","primary_location":{"id":"doi:10.1145/3627673.3679987","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679987","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3627673.3679987","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002039283","display_name":"Dairui Liu","orcid":"https://orcid.org/0000-0002-8573-3857"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":true,"raw_author_name":"Dairui Liu","raw_affiliation_strings":["University College Dublin, Dublin, Ireland"],"affiliations":[{"raw_affiliation_string":"University College Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001872756","display_name":"Boming Yang","orcid":"https://orcid.org/0009-0004-6298-5711"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Boming Yang","raw_affiliation_strings":["The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048898655","display_name":"Honghui Du","orcid":"https://orcid.org/0000-0001-8758-0092"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Honghui Du","raw_affiliation_strings":["University College Dublin, Dublin, Ireland"],"affiliations":[{"raw_affiliation_string":"University College Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053619267","display_name":"Derek Greene","orcid":"https://orcid.org/0000-0001-8065-5418"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Derek Greene","raw_affiliation_strings":["University College Dublin, Dublin, Ireland"],"affiliations":[{"raw_affiliation_string":"University College Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084111561","display_name":"Neil Hurley","orcid":"https://orcid.org/0000-0001-8428-2866"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Neil Hurley","raw_affiliation_strings":["University College Dublin, Dublin, Ireland"],"affiliations":[{"raw_affiliation_string":"University College Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079971230","display_name":"Aonghus Lawlor","orcid":"https://orcid.org/0000-0002-6160-4639"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Aonghus Lawlor","raw_affiliation_strings":["University College Dublin, Dublin, Ireland"],"affiliations":[{"raw_affiliation_string":"University College Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009000289","display_name":"Ruihai Dong","orcid":"https://orcid.org/0000-0002-2509-1370"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Ruihai Dong","raw_affiliation_strings":["University College Dublin, Dublin, Ireland"],"affiliations":[{"raw_affiliation_string":"University College Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101537931","display_name":"Irene Li","orcid":"https://orcid.org/0000-0002-1851-5390"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Irene Li","raw_affiliation_strings":["University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5002039283"],"corresponding_institution_ids":["https://openalex.org/I100930933"],"apc_list":null,"apc_paid":null,"fwci":4.9345,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.95807287,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3902","last_page":"3906"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8079705834388733},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.6275313496589661},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4228697717189789},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.38732388615608215},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3716854751110077},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.36445146799087524},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.329464852809906},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.24977397918701172}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8079705834388733},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.6275313496589661},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4228697717189789},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38732388615608215},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3716854751110077},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.36445146799087524},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.329464852809906},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.24977397918701172}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3627673.3679987","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679987","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3627673.3679987","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679987","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2950416834","https://openalex.org/W2950421571","https://openalex.org/W2963869731","https://openalex.org/W2970793364","https://openalex.org/W3034503922","https://openalex.org/W4223982309","https://openalex.org/W4285217136","https://openalex.org/W4290945693","https://openalex.org/W4368755500","https://openalex.org/W4386729896","https://openalex.org/W4392366624","https://openalex.org/W4393982454","https://openalex.org/W4401042327"],"related_works":["https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405","https://openalex.org/W2056712470","https://openalex.org/W3125580266","https://openalex.org/W4317039510","https://openalex.org/W4238861846","https://openalex.org/W790944756"],"abstract_inverted_index":{"News":[0],"recommendations":[1,95],"heavily":[2],"rely":[3],"on":[4,20],"Natural":[5],"Language":[6,27],"Processing":[7],"(NLP)":[8],"methods":[9],"to":[10,46,51,71,93,128,139,146],"analyze,":[11],"understand,":[12],"and":[13,23,83,123,164],"categorize":[14],"content,":[15],"enabling":[16],"personalized":[17],"suggestions":[18],"based":[19],"user":[21],"interests":[22],"reading":[24],"behaviors.":[25],"Large":[26],"Models":[28],"(LLMs)":[29],"like":[30],"GPT-4":[31],"have":[32],"shown":[33],"promising":[34],"performance":[35],"in":[36,115,118,121,125,158],"understanding":[37],"natural":[38],"language.":[39],"However,":[40],"the":[41,58,67],"extent":[42],"of":[43,69,113,149,162],"their":[44],"applicability":[45],"news":[47,64,74,81],"recommendation":[48,75],"systems":[49],"remains":[50],"be":[52],"validated.":[53],"This":[54,77],"paper":[55],"introduces":[56],"RecPrompt,":[57],"first":[59],"self-tuning":[60],"prompting":[61],"framework":[62,78],"for":[63,151],"recommendation,":[65],"leveraging":[66],"capabilities":[68],"LLMs":[70],"perform":[72],"complex":[73],"tasks.":[76],"incorporates":[79],"a":[80,84,136],"recommender":[82],"prompt":[85,98],"optimizer":[86],"that":[87,107],"applies":[88],"an":[89,111],"iterative":[90],"bootstrapping":[91],"process":[92],"enhance":[94],"through":[96],"automatic":[97],"engineering.":[99],"Extensive":[100],"experimental":[101],"results":[102,154],"with":[103],"400":[104],"users":[105],"show":[106,155],"RecPrompt":[108],"can":[109],"achieve":[110],"improvement":[112],"3.36%":[114],"AUC,":[116],"10.49%":[117],"MRR,":[119],"9.64%":[120],"nDCG@5,":[122],"6.20%":[124],"nDCG@10":[126],"compared":[127],"deep":[129],"neural":[130],"models.":[131],"Additionally,":[132],"we":[133],"introduce":[134],"TopicScore,":[135],"novel":[137],"metric":[138],"assess":[140],"explainability":[141],"by":[142],"evaluating":[143],"LLM's":[144,156],"ability":[145],"summarize":[147],"topics":[148,161],"interest":[150,163],"users.":[152],"The":[153],"effectiveness":[157],"accurately":[159],"identifying":[160],"delivering":[165],"comprehensive":[166],"topic-based":[167],"explanations.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":11}],"updated_date":"2026-03-24T08:02:53.985720","created_date":"2025-10-10T00:00:00"}