{"id":"https://openalex.org/W4403577470","doi":"https://doi.org/10.1145/3627673.3679945","title":"Improving Prompt-based News Recommendation with Individual Template and Customized Answer","display_name":"Improving Prompt-based News Recommendation with Individual Template and Customized Answer","publication_year":2024,"publication_date":"2024-10-20","ids":{"openalex":"https://openalex.org/W4403577470","doi":"https://doi.org/10.1145/3627673.3679945"},"language":"en","primary_location":{"id":"doi:10.1145/3627673.3679945","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627673.3679945","pdf_url":null,"source":null,"license":null,"license_id":null,"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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104331146","display_name":"Yijiang Li","orcid":"https://orcid.org/0009-0005-1733-5645"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yijiang Li","raw_affiliation_strings":["MoE Key Lab of Big Data & Artificial Intelligence in Transportation, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"MoE Key Lab of Big Data & Artificial Intelligence in Transportation, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100702644","display_name":"Jun Wu","orcid":"https://orcid.org/0000-0001-5733-3621"},"institutions":[{"id":"https://openalex.org/I161222507","display_name":"Open University of China","ror":"https://ror.org/02maxav80","country_code":"CN","type":"education","lineage":["https://openalex.org/I161222507"]},{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Wu","raw_affiliation_strings":["MoE Key Lab of Big Data & Artificial Intelligence in Transportation, Beijing Jiaotong University & MoE Engineering Research Center of Integration and Application of Digital Learning Technology, The Open University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"MoE Key Lab of Big Data & Artificial Intelligence in Transportation, Beijing Jiaotong University & MoE Engineering Research Center of Integration and Application of Digital Learning Technology, The Open University of China, Beijing, China","institution_ids":["https://openalex.org/I161222507","https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5104331146"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":0.7049,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.76558276,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3887","last_page":"3891"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9984999895095825,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9983000159263611,"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":0.8033527135848999},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5973186492919922},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4473855495452881},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.38503408432006836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8033527135848999},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5973186492919922},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4473855495452881},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.38503408432006836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3627673.3679945","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627673.3679945","pdf_url":null,"source":null,"license":null,"license_id":null,"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":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2246362147","https://openalex.org/W2950416834","https://openalex.org/W2963869731","https://openalex.org/W2964536660","https://openalex.org/W2988777870","https://openalex.org/W3034236656","https://openalex.org/W3098267758","https://openalex.org/W3153427360","https://openalex.org/W3155368131","https://openalex.org/W3185341429","https://openalex.org/W4230636291","https://openalex.org/W4284707744","https://openalex.org/W4285295485","https://openalex.org/W4290945693","https://openalex.org/W4365211555","https://openalex.org/W4384661062"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","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"],"abstract_inverted_index":{"Prompt":[0,50],"learning":[1],"plays":[2],"a":[3,88,97,106],"key":[4],"role":[5],"in":[6],"aligning":[7],"the":[8,15,32,38,72,115,124],"task":[9],"of":[10,34,74,99,117],"news":[11,41],"recommendation":[12],"(NR)":[13],"with":[14,134],"Pre-trained":[16],"Language":[17],"Models":[18],"(PLMs).":[19],"However,":[20],"current":[21],"prompt-based":[22],"NR":[23,52,141],"methods":[24],"utilize":[25],"fixed":[26],"templates":[27,59],"and":[28,37,67,137],"answer":[29,69,101],"words,":[30],"ignoring":[31],"personalization":[33],"user's":[35,89],"demand":[36],"diversity":[39],"between":[40],"topics.":[42],"To":[43],"this":[44],"end,":[45],"we":[46,127],"propose":[47],"an":[48,79],"Automatic":[49],"based":[51,113],"(AutoPNR)":[53],"scheme,":[54],"which":[55],"automatically":[56],"generates":[57],"individual":[58,80],"for":[60],"users":[61],"according":[62],"to":[63,86],"their":[64],"potential":[65],"interests,":[66],"customized":[68,100],"words":[70,102],"w.r.t.":[71],"topics":[73],"candidate":[75,118],"news.":[76,119],"Concretely,":[77],"such":[78],"template":[81],"utilizes":[82],"several":[83],"specific":[84],"tokens":[85],"encode":[87],"interest":[90],"extracted":[91],"from":[92,105],"her/his":[93],"reading":[94],"history,":[95],"while":[96],"pair":[98],"are":[103],"retrieved":[104],"large":[107],"vocabulary":[108],"(often":[109],"existing":[110],"alongside":[111],"PLMs)":[112],"on":[114,123],"topic":[116],"Through":[120],"extensive":[121],"experiments":[122],"real-world":[125],"datasets,":[126],"show":[128],"that":[129],"our":[130],"AutoPNR":[131],"works":[132],"well":[133],"different":[135],"PLMs,":[136],"considerably":[138],"outperforms":[139],"state-of-the-art":[140],"techniques.":[142]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-24T08:02:53.985720","created_date":"2025-10-10T00:00:00"}