{"id":"https://openalex.org/W4385565448","doi":"https://doi.org/10.1145/3580305.3599502","title":"Shilling Black-box Review-based Recommender Systems through Fake Review Generation","display_name":"Shilling Black-box Review-based Recommender Systems through Fake Review Generation","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385565448","doi":"https://doi.org/10.1145/3580305.3599502"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599502","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599502","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery 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/A5018161865","display_name":"Hung-Yun Chiang","orcid":"https://orcid.org/0009-0009-0940-1816"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Hung-Yun Chiang","raw_affiliation_strings":["National Tsing Hua University, HsinChu, Taiwan Roc"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, HsinChu, Taiwan Roc","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071371624","display_name":"Yi-Syuan Chen","orcid":"https://orcid.org/0000-0003-3233-020X"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yi-Syuan Chen","raw_affiliation_strings":["National Yang Ming Chiao Tung University, HsinChu, Taiwan Roc"],"affiliations":[{"raw_affiliation_string":"National Yang Ming Chiao Tung University, HsinChu, Taiwan Roc","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069080179","display_name":"Yun-Zhu Song","orcid":"https://orcid.org/0000-0003-4542-8505"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yun-Zhu Song","raw_affiliation_strings":["National Yang Ming Chiao Tung University, HsinChu, Taiwan Roc"],"affiliations":[{"raw_affiliation_string":"National Yang Ming Chiao Tung University, HsinChu, Taiwan Roc","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040050806","display_name":"Hong-Han Shuai","orcid":"https://orcid.org/0000-0003-2216-077X"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hong-Han Shuai","raw_affiliation_strings":["National Yang Ming Chiao Tung University, HsinChu, Taiwan Roc"],"affiliations":[{"raw_affiliation_string":"National Yang Ming Chiao Tung University, HsinChu, Taiwan Roc","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016135743","display_name":"Jason S. Chang","orcid":"https://orcid.org/0000-0002-8227-7382"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jason S. Chang","raw_affiliation_strings":["National Tsing Hua University, HsinChu, Taiwan Roc"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, HsinChu, Taiwan Roc","institution_ids":["https://openalex.org/I25846049"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5018161865"],"corresponding_institution_ids":["https://openalex.org/I25846049"],"apc_list":null,"apc_paid":null,"fwci":1.8054,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.87383618,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"286","last_page":"297"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9965000152587891,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9952999949455261,"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":0.8363893032073975},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.7714956998825073},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6794429421424866},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.6238874197006226},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6015441417694092},{"id":"https://openalex.org/keywords/fluency","display_name":"Fluency","score":0.5826867818832397},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.542258083820343},{"id":"https://openalex.org/keywords/forcing","display_name":"Forcing (mathematics)","score":0.466448038816452},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.453750878572464},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.401265025138855}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8363893032073975},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7714956998825073},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6794429421424866},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6238874197006226},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6015441417694092},{"id":"https://openalex.org/C2777413886","wikidata":"https://www.wikidata.org/wiki/Q3276013","display_name":"Fluency","level":2,"score":0.5826867818832397},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.542258083820343},{"id":"https://openalex.org/C197115733","wikidata":"https://www.wikidata.org/wiki/Q1003136","display_name":"Forcing (mathematics)","level":2,"score":0.466448038816452},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.453750878572464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.401265025138855},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C49204034","wikidata":"https://www.wikidata.org/wiki/Q52139","display_name":"Climatology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3580305.3599502","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599502","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8299999833106995,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1989279326","https://openalex.org/W2029046707","https://openalex.org/W2029424893","https://openalex.org/W2075446120","https://openalex.org/W2119717200","https://openalex.org/W2165112010","https://openalex.org/W2171960770","https://openalex.org/W2200988052","https://openalex.org/W2578245359","https://openalex.org/W2788376297","https://openalex.org/W2799194071","https://openalex.org/W2809686659","https://openalex.org/W2890009645","https://openalex.org/W2945996535","https://openalex.org/W2947936100","https://openalex.org/W2963084599","https://openalex.org/W2982756474","https://openalex.org/W3025378468","https://openalex.org/W3031339255","https://openalex.org/W3034214559","https://openalex.org/W3098648976","https://openalex.org/W3104956872","https://openalex.org/W3118081178","https://openalex.org/W3154925836","https://openalex.org/W3174112555","https://openalex.org/W3175747747","https://openalex.org/W3195126378","https://openalex.org/W3198269165","https://openalex.org/W3198859314","https://openalex.org/W4200626973","https://openalex.org/W4225109328","https://openalex.org/W4283445889","https://openalex.org/W4283650725","https://openalex.org/W4286750695","https://openalex.org/W6732330094"],"related_works":["https://openalex.org/W2968745142","https://openalex.org/W2809363009","https://openalex.org/W2369936857","https://openalex.org/W2348159088","https://openalex.org/W2045871438","https://openalex.org/W3046843850","https://openalex.org/W4386716251","https://openalex.org/W4306789193","https://openalex.org/W3208312582","https://openalex.org/W4226067002"],"abstract_inverted_index":{"Review-Based":[0],"Recommender":[1],"Systems":[2],"(RBRS)":[3],"have":[4],"attracted":[5],"increasing":[6],"research":[7],"interest":[8],"due":[9],"to":[10,13,21,44,90,98,178],"their":[11],"ability":[12],"alleviate":[14],"well-known":[15],"cold-start":[16],"problems.":[17],"RBRS":[18],"utilizes":[19],"reviews":[20,39,89,116,158],"construct":[22],"the":[23,45,59,91,95,105,114,129,141,156],"user":[24],"and":[25,102,111,147,161],"items":[26,81],"representations.":[27],"However,":[28],"in":[29,54],"this":[30,52,55],"paper,":[31,56],"we":[32,57,69],"argue":[33],"that":[34,128,155],"such":[35],"a":[36,71],"reliance":[37],"on":[38,140],"may":[40],"instead":[41],"expose":[42],"systems":[43],"risk":[46],"of":[47,107,138],"being":[48],"shilled.":[49],"To":[50],"explore":[51],"possibility,":[53],"propose":[58],"first":[60],"generation-based":[61],"model":[62],"for":[63,120],"shilling":[64,121],"attacks":[65],"against":[66],"RBRSs.":[67],"Specifically,":[68],"learn":[70],"fake":[72],"review":[73],"generator":[74],"through":[75],"reinforcement":[76],"learning,":[77],"which":[78],"maliciously":[79],"promotes":[80],"by":[82],"forcing":[83],"prediction":[84],"shifts":[85],"after":[86],"adding":[87],"generated":[88,115,157],"system.":[92],"By":[93],"introducing":[94],"auxiliary":[96],"rewards":[97],"increase":[99],"text":[100],"fluency":[101],"diversity":[103],"with":[104,122,144,165,171],"aid":[106],"pre-trained":[108],"language":[109],"models":[110],"aspect":[112],"predictors,":[113],"can":[117,132],"be":[118],"effective":[119],"high":[123],"fidelity.":[124],"Experimental":[125],"results":[126],"demonstrate":[127],"proposed":[130],"framework":[131],"successfully":[133],"attack":[134],"three":[135,145],"different":[136],"kinds":[137],"RBRSs":[139,170],"Amazon":[142],"corpus":[143],"domains":[146],"Yelp":[148],"corpus.":[149],"Furthermore,":[150],"human":[151],"studies":[152],"also":[153],"show":[154],"are":[159,174],"fluent":[160],"informative.":[162],"Finally,":[163],"equipped":[164],"Attack":[166],"Review":[167],"Generators":[168],"(ARGs),":[169],"adversarial":[172],"training":[173],"much":[175],"more":[176],"robust":[177],"malicious":[179],"reviews.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
