{"id":"https://openalex.org/W4386729425","doi":"https://doi.org/10.1145/3604915.3608884","title":"Denoising Explicit Social Signals for Robust Recommendation","display_name":"Denoising Explicit Social Signals for Robust Recommendation","publication_year":2023,"publication_date":"2023-09-14","ids":{"openalex":"https://openalex.org/W4386729425","doi":"https://doi.org/10.1145/3604915.3608884"},"language":"en","primary_location":{"id":"doi:10.1145/3604915.3608884","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3604915.3608884","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM Conference on Recommender Systems","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/A5003439728","display_name":"Youchen Sun","orcid":"https://orcid.org/0000-0001-6164-5361"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Youchen Sun","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-6164-5361","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5003439728"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":4.0358,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.94507814,"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":"1344","last_page":"1348"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":0.9843000173568726,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6169707775115967},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5372920036315918},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4428809583187103},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.41929009556770325},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37569350004196167},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.34349292516708374},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.2253682017326355}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6169707775115967},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5372920036315918},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4428809583187103},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.41929009556770325},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37569350004196167},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34349292516708374},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2253682017326355},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3604915.3608884","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3604915.3608884","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM Conference on Recommender Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W2093219534","https://openalex.org/W2119825970","https://openalex.org/W2144487656","https://openalex.org/W2244405900","https://openalex.org/W2509678028","https://openalex.org/W2533413719","https://openalex.org/W2604175478","https://openalex.org/W2754493004","https://openalex.org/W2788872664","https://openalex.org/W2798868970","https://openalex.org/W2890884621","https://openalex.org/W2896367309","https://openalex.org/W2899291427","https://openalex.org/W2903665338","https://openalex.org/W2911319979","https://openalex.org/W2914721378","https://openalex.org/W2962907114","https://openalex.org/W2965021023","https://openalex.org/W2965209830","https://openalex.org/W2971600245","https://openalex.org/W3010088852","https://openalex.org/W3033630125","https://openalex.org/W3035589558","https://openalex.org/W3045200674","https://openalex.org/W3088444111","https://openalex.org/W3094605801","https://openalex.org/W3095937012","https://openalex.org/W3099939189","https://openalex.org/W3109948242","https://openalex.org/W3116172555","https://openalex.org/W3153325943","https://openalex.org/W3155496675","https://openalex.org/W3170682786","https://openalex.org/W3197317754","https://openalex.org/W3206458369","https://openalex.org/W3210628790","https://openalex.org/W4205132462","https://openalex.org/W4223969322","https://openalex.org/W4327668311"],"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":{"Social":[0],"recommender":[1],"system":[2],"assumes":[3],"that":[4,24,59,87,95,119],"user\u2019s":[5],"preferences":[6],"can":[7,98],"be":[8,164],"influenced":[9],"by":[10],"their":[11],"social":[12,15,46,64,85,101,126,183],"connections.":[13],"However,":[14],"networks":[16],"are":[17,25,56,60,83,88],"inherently":[18],"noisy":[19,125,142],"and":[20,51,144,156],"contain":[21],"redundant":[22],"signals":[23,143],"not":[26,68],"helpful":[27],"or":[28],"even":[29],"harmful":[30],"for":[31,170],"the":[32,41,44,63,73,80,96,100,105,124,131,139,158,167,171,178,188,199],"recommendation":[33,106],"task.":[34],"In":[35],"this":[36,110],"extended":[37],"abstract,":[38],"we":[39,112,129,186],"classify":[40],"noise":[42,50,197],"in":[43,62],"explicit":[45],"links":[47,86],"into":[48],"intrinsic":[49],"extrinsic":[52,196],"noise.":[53],"Intrinsic":[54],"noises":[55],"those":[57,84],"edges":[58],"natural":[61],"network":[65],"but":[66],"do":[67],"have":[69],"an":[70,148],"influence":[71,102,132],"on":[72,79,166],"user":[74,153],"preference":[75,154],"modeling;":[76],"Extrinsic":[77],"noises,":[78],"other":[81],"hand,":[82],"introduced":[89],"intentionally":[90],"through":[91,202],"malicious":[92],"attacks":[93],"such":[94],"attackers":[97],"manipulate":[99],"to":[103,121,137,151,181,193],"bias":[104],"outcome.":[107],"To":[108],"tackle":[109],"issue,":[111],"first":[113],"propose":[114],"a":[115],"self-supervised":[116],"denoising":[117],"framework":[118],"learns":[120],"filter":[122],"out":[123],"edges.":[127],"Specifically,":[128],"introduce":[130],"of":[133,141],"key":[134],"opinion":[135],"leaders":[136],"hinder":[138],"diffusion":[140],"also":[145],"function":[146],"as":[147,175,177],"extra":[149],"source":[150],"enhance":[152],"modeling":[155],"alleviate":[157],"data":[159],"sparsity":[160],"issue.":[161],"Experiments":[162],"will":[163],"conducted":[165],"real-world":[168],"datasets":[169],"Top-K":[172],"ranking":[173],"evaluation":[174],"well":[176],"model\u2019s":[179],"robustness":[180],"simulated":[182],"noises.":[184],"Finally,":[185],"discuss":[187],"future":[189],"plan":[190],"about":[191],"how":[192],"defend":[194],"against":[195],"from":[198],"attacker\u2019s":[200],"perspective":[201],"adversarial":[203],"training.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
