{"id":"https://openalex.org/W4321485456","doi":"https://doi.org/10.1145/3539597.3570447","title":"Improving News Recommendation with Channel-Wise Dynamic Representations and Contrastive User Modeling","display_name":"Improving News Recommendation with Channel-Wise Dynamic Representations and Contrastive User Modeling","publication_year":2023,"publication_date":"2023-02-22","ids":{"openalex":"https://openalex.org/W4321485456","doi":"https://doi.org/10.1145/3539597.3570447"},"language":"en","primary_location":{"id":"doi:10.1145/3539597.3570447","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539597.3570447","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","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/A5058641372","display_name":"Jingkun Wang","orcid":"https://orcid.org/0000-0002-8658-9690"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingkun Wang","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8658-9690","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000036456","display_name":"Yongtao Jiang","orcid":"https://orcid.org/0000-0002-9868-9445"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongtao Jiang","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9868-9445","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100742023","display_name":"Haochen Li","orcid":"https://orcid.org/0000-0002-3197-4073"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haochen Li","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3197-4073","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101405285","display_name":"Wen Zhao","orcid":"https://orcid.org/0000-0002-5760-4759"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Zhao","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5760-4759","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":6.8364,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.96784172,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"562","last_page":"570"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9990000128746033,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9916999936103821,"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":0.8828940391540527},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6356887817382812},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.49363815784454346},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.4829239547252655},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4819028675556183},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.46709316968917847},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.44674810767173767},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4450572431087494},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4321177005767822},{"id":"https://openalex.org/keywords/user-modeling","display_name":"User modeling","score":0.42872992157936096},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4236447811126709},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39871805906295776},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39454150199890137},{"id":"https://openalex.org/keywords/user-interface","display_name":"User interface","score":0.19933462142944336},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09473901987075806},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.08960670232772827}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8828940391540527},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6356887817382812},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.49363815784454346},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.4829239547252655},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4819028675556183},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.46709316968917847},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.44674810767173767},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4450572431087494},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4321177005767822},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.42872992157936096},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4236447811126709},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39871805906295776},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39454150199890137},{"id":"https://openalex.org/C89505385","wikidata":"https://www.wikidata.org/wiki/Q47146","display_name":"User interface","level":2,"score":0.19933462142944336},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09473901987075806},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08960670232772827},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3539597.3570447","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539597.3570447","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3967313144","display_name":null,"funder_award_id":"2020YFC0833300","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2094286023","https://openalex.org/W2136189984","https://openalex.org/W2531409750","https://openalex.org/W2903803738","https://openalex.org/W2950416834","https://openalex.org/W3014828506","https://openalex.org/W3034236656","https://openalex.org/W3034449195","https://openalex.org/W3034503922","https://openalex.org/W3103448498","https://openalex.org/W3106127452","https://openalex.org/W3154394390","https://openalex.org/W3182452706","https://openalex.org/W4213052788","https://openalex.org/W4230636291","https://openalex.org/W4233366162","https://openalex.org/W4238216513","https://openalex.org/W4240935049","https://openalex.org/W4288269198"],"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/W2537376277","https://openalex.org/W2171641484","https://openalex.org/W2561634757"],"abstract_inverted_index":{"News":[0],"modeling":[1,4],"and":[2,16,41,50,64,81,106,148],"user":[3,14,143,146,156,166],"are":[5,82,123],"the":[6,21,58,74,135,141,150,173],"two":[7],"core":[8],"tasks":[9],"of":[10,152,175],"news":[11,17,48,55,120],"recommendation.":[12],"Accurate":[13],"representation":[15,18],"can":[19],"enable":[20],"recommendation":[22,29],"system":[23],"to":[24,43,52,84,99,139],"provide":[25],"users":[26,114],"with":[27],"precise":[28],"services.":[30],"Most":[31],"existing":[32],"methods":[33,60,76],"use":[34],"deep":[35],"learning":[36,163],"models":[37],"such":[38],"as":[39],"CNN":[40],"Self-Attention":[42],"extract":[44,66,107],"text":[45],"features":[46,68,87,109],"from":[47,110],"titles":[49],"abstracts":[51],"generate":[53,100],"specific":[54,67],"vectors.":[56],"However,":[57],"CNN-based":[59],"have":[61,77],"fixed":[62],"parameters":[63,102],"cannot":[65],"for":[69,103],"different":[70,104],"input":[71],"words,":[72],"while":[73],"Self-Attention-based":[75],"high":[78],"computational":[79],"costs":[80],"difficult":[83],"capture":[85],"local":[86,108],"effectively.":[88],"In":[89,137],"our":[90,176],"proposed":[91,177],"method,":[92],"we":[93,158],"build":[94],"a":[95,160],"category-based":[96],"dynamic":[97],"component":[98],"suitable":[101],"inputs":[105],"multiple":[111],"perspectives.":[112],"Meanwhile,":[113],"will":[115,129],"mistakenly":[116],"click":[117],"on":[118,155,169],"some":[119,131],"terms":[121],"they":[122],"not":[124],"interested":[125],"in,":[126],"so":[127],"there":[128],"be":[130],"interaction":[132],"noises":[133],"in":[134,145,165],"datasets.":[136],"order":[138],"explore":[140],"critical":[142],"behaviors":[144],"data":[147,154],"reduce":[149],"impact":[151],"noise":[153],"modeling,":[157],"adopt":[159],"frequency-aware":[161],"contrastive":[162],"method":[164],"modeling.":[167],"Experiments":[168],"real-world":[170],"datasets":[171],"verify":[172],"effectiveness":[174],"method.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
