{"id":"https://openalex.org/W7163024719","doi":"https://doi.org/10.1145/3774935.3812713","title":"PerSpect: Perspective-aware Contrastive Learning for Hybrid News Recommendation","display_name":"PerSpect: Perspective-aware Contrastive Learning for Hybrid News Recommendation","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7163024719","doi":"https://doi.org/10.1145/3774935.3812713"},"language":null,"primary_location":{"id":"doi:10.1145/3774935.3812713","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774935.3812713","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 34th ACM Conference on User Modeling, Adaptation and Personalization","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774935.3812713","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053523229","display_name":"Payam Pourashraf","orcid":null},"institutions":[{"id":"https://openalex.org/I118353179","display_name":"DePaul University","ror":"https://ror.org/04xtx5t16","country_code":"US","type":"education","lineage":["https://openalex.org/I118353179"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Payam Pourashraf","raw_affiliation_strings":["DePaul University, Chicago, IL, USA"],"raw_orcid":"https://orcid.org/0009-0000-6019-7755","affiliations":[{"raw_affiliation_string":"DePaul University, Chicago, IL, USA","institution_ids":["https://openalex.org/I118353179"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009118126","display_name":"Masoud Mansoury","orcid":"https://orcid.org/0000-0002-9938-0212"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Masoud Mansoury","raw_affiliation_strings":["Delft University of Technology, Delft, Netherlands"],"raw_orcid":"https://orcid.org/0000-0002-9938-0212","affiliations":[{"raw_affiliation_string":"Delft University of Technology, Delft, Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082580430","display_name":"Bamshad Mobasher","orcid":"https://orcid.org/0000-0001-9701-9178"},"institutions":[{"id":"https://openalex.org/I118353179","display_name":"DePaul University","ror":"https://ror.org/04xtx5t16","country_code":"US","type":"education","lineage":["https://openalex.org/I118353179"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bamshad Mobasher","raw_affiliation_strings":["DePaul University, Chicago, IL, USA"],"raw_orcid":"https://orcid.org/0000-0001-9701-9178","affiliations":[{"raw_affiliation_string":"DePaul University, Chicago, IL, USA","institution_ids":["https://openalex.org/I118353179"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"532","last_page":"535"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.2964000105857849,"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":0.2964000105857849,"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/T14074","display_name":"Persona Design and Applications","score":0.16339999437332153,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.08699999749660492,"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/session","display_name":"Session (web analytics)","score":0.6190000176429749},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5509999990463257},{"id":"https://openalex.org/keywords/prefix","display_name":"Prefix","score":0.48820000886917114},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.40860000252723694},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4049000144004822},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.375900000333786},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3246999979019165}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6740000247955322},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.6190000176429749},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5860999822616577},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5649999976158142},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5509999990463257},{"id":"https://openalex.org/C141603448","wikidata":"https://www.wikidata.org/wiki/Q134830","display_name":"Prefix","level":2,"score":0.48820000886917114},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.40860000252723694},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4049000144004822},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.38269999623298645},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.375900000333786},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32330000400543213},{"id":"https://openalex.org/C2777629044","wikidata":"https://www.wikidata.org/wiki/Q614959","display_name":"Contrastive analysis","level":2,"score":0.31679999828338623},{"id":"https://openalex.org/C313442","wikidata":"https://www.wikidata.org/wiki/Q778556","display_name":"Persona","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C2780876879","wikidata":"https://www.wikidata.org/wiki/Q3054749","display_name":"Meaning (existential)","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C2777601897","wikidata":"https://www.wikidata.org/wiki/Q3409113","display_name":"Presentation (obstetrics)","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.2590000033378601}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3774935.3812713","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774935.3812713","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 34th ACM Conference on User Modeling, Adaptation and Personalization","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3774935.3812713","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774935.3812713","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 34th ACM Conference on User Modeling, Adaptation and Personalization","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8770751357078552}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2809307135","https://openalex.org/W2964536660","https://openalex.org/W2984100107","https://openalex.org/W3065542300","https://openalex.org/W3133849783","https://openalex.org/W4223982309","https://openalex.org/W4281656714","https://openalex.org/W4386352396","https://openalex.org/W4387461044","https://openalex.org/W4403319954","https://openalex.org/W4403577379","https://openalex.org/W4404781003"],"related_works":[],"abstract_inverted_index":{"Local":[0],"news":[1,16],"recommendation":[2],"must":[3],"model":[4],"both":[5,123],"immediate":[6],"reading":[7],"intent":[8],"and":[9,14,76,90,101,120,125,145],"users\u2019":[10],"mix":[11],"of":[12,43],"local":[13],"nonlocal":[15],"consumption.":[17],"We":[18,51,68],"present":[19],"PerSpect,":[20],"a":[21,78,138],"hybrid":[22],"framework":[23],"that":[24,63,147],"builds":[25],"semantically":[26],"meaningful":[27],"contrastive":[28,85],"views":[29,136],"from":[30],"category\u2013locality":[31],"specialist":[32],"models.":[33],"Our":[34],"main":[35],"method,":[36],"Cross-Submodel":[37,54],"Contrastive":[38,56],"learning":[39,57],"(CSC),":[40],"contrasts":[41],"embeddings":[42],"the":[44,72,107,112,128],"same":[45],"session":[46],"produced":[47],"by":[48],"different":[49],"specialists.":[50],"also":[52],"study":[53],"Persona":[55],"(CSPC)":[58],"as":[59,137],"an":[60],"exploratory":[61],"extension":[62],"adds":[64],"same-persona,":[65],"different-user":[66],"positives.":[67],"evaluate":[69],"PerSpect":[70],"on":[71,77,127],"real-world":[73],"EB-NeRD":[74,109],"dataset":[75],"synthetic":[79,129],"Syracuse":[80],"benchmark":[81],"against":[82],"session-based":[83],"baselines,":[84,87,89],"augmentation":[86],"late-fusion":[88],"fusion-only":[91],"ablations.":[92],"Experiments":[93],"use":[94],"train-only":[95],"persona":[96],"construction,":[97],"fixed":[98],"candidate":[99],"sets,":[100],"prefix-based":[102],"next-item":[103],"evaluation.":[104],"CSC":[105,119],"obtains":[106],"strongest":[108],"results":[110],"in":[111],"reported":[113],"full":[114],"prefix":[115],"train/eval":[116],"setting,":[117],"while":[118],"CSPC":[121],"are":[122,150],"strong":[124],"close":[126],"benchmark.":[130],"These":[131],"findings":[132],"support":[133],"specialist-derived":[134],"semantic":[135],"promising":[139],"alternative":[140],"to":[141],"random":[142],"sequence":[143],"augmentations":[144],"show":[146],"persona-aware":[148],"positives":[149],"useful":[151],"but":[152],"dataset-dependent.":[153]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-06-02T00:00:00"}
