{"id":"https://openalex.org/W2075807628","doi":"https://doi.org/10.1145/1148170.1148259","title":"Analysis of a low-dimensional linear model under recommendation attacks","display_name":"Analysis of a low-dimensional linear model under recommendation attacks","publication_year":2006,"publication_date":"2006-08-06","ids":{"openalex":"https://openalex.org/W2075807628","doi":"https://doi.org/10.1145/1148170.1148259","mag":"2075807628"},"language":"en","primary_location":{"id":"doi:10.1145/1148170.1148259","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1148170.1148259","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 annual international ACM SIGIR conference on Research and development in information retrieval","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100394010","display_name":"Sheng Zhang","orcid":"https://orcid.org/0000-0002-1993-1660"},"institutions":[{"id":"https://openalex.org/I107672454","display_name":"Dartmouth College","ror":"https://ror.org/049s0rh22","country_code":"US","type":"education","lineage":["https://openalex.org/I107672454"]},{"id":"https://openalex.org/I4210166639","display_name":"Dartmouth Hospital","ror":"https://ror.org/02j3qj605","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210166639"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Sheng Zhang","raw_affiliation_strings":["Dartmouth College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dartmouth College","institution_ids":["https://openalex.org/I107672454","https://openalex.org/I4210166639"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102758747","display_name":"Yi Ouyang","orcid":"https://orcid.org/0000-0001-5987-451X"},"institutions":[{"id":"https://openalex.org/I107672454","display_name":"Dartmouth College","ror":"https://ror.org/049s0rh22","country_code":"US","type":"education","lineage":["https://openalex.org/I107672454"]},{"id":"https://openalex.org/I4210166639","display_name":"Dartmouth Hospital","ror":"https://ror.org/02j3qj605","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210166639"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Yi Ouyang","raw_affiliation_strings":["Dartmouth College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dartmouth College","institution_ids":["https://openalex.org/I107672454","https://openalex.org/I4210166639"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030044963","display_name":"James Ford","orcid":"https://orcid.org/0000-0001-8044-6536"},"institutions":[{"id":"https://openalex.org/I107672454","display_name":"Dartmouth College","ror":"https://ror.org/049s0rh22","country_code":"US","type":"education","lineage":["https://openalex.org/I107672454"]},{"id":"https://openalex.org/I4210166639","display_name":"Dartmouth Hospital","ror":"https://ror.org/02j3qj605","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210166639"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"James Ford","raw_affiliation_strings":["Dartmouth College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dartmouth College","institution_ids":["https://openalex.org/I107672454","https://openalex.org/I4210166639"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044363105","display_name":"Fillia Makedon","orcid":"https://orcid.org/0009-0001-8831-6872"},"institutions":[{"id":"https://openalex.org/I107672454","display_name":"Dartmouth College","ror":"https://ror.org/049s0rh22","country_code":"US","type":"education","lineage":["https://openalex.org/I107672454"]},{"id":"https://openalex.org/I4210166639","display_name":"Dartmouth Hospital","ror":"https://ror.org/02j3qj605","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210166639"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Fillia Makedon","raw_affiliation_strings":["Dartmouth College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dartmouth College","institution_ids":["https://openalex.org/I107672454","https://openalex.org/I4210166639"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.9605,"has_fulltext":false,"cited_by_count":79,"citation_normalized_percentile":{"value":0.97652908,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9860000014305115,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9860000014305115,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9854000210762024,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9666000008583069,"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":0.6090226173400879}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6090226173400879}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1148170.1148259","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1148170.1148259","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 annual international ACM SIGIR conference on Research and development in information retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4000000059604645,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W145109340","https://openalex.org/W1586776267","https://openalex.org/W1673941785","https://openalex.org/W1832221731","https://openalex.org/W2000855935","https://openalex.org/W2021680564","https://openalex.org/W2042281163","https://openalex.org/W2049455633","https://openalex.org/W2070786785","https://openalex.org/W2072651985","https://openalex.org/W2085937320","https://openalex.org/W2109992782","https://openalex.org/W2117354486","https://openalex.org/W2144194596","https://openalex.org/W2151052953","https://openalex.org/W2155106456","https://openalex.org/W2158515176","https://openalex.org/W2165395308","https://openalex.org/W2167680278","https://openalex.org/W2169305649","https://openalex.org/W2913668833","https://openalex.org/W2913838200","https://openalex.org/W4232980324","https://openalex.org/W6637259173"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W2530322880"],"abstract_inverted_index":{"Collaborative":[0],"filtering":[1,29,52],"techniques":[2],"have":[3,43],"become":[4],"popular":[5,60],"in":[6,27,33],"the":[7,56,67,90,113],"past":[8],"decade":[9],"as":[10],"an":[11,106],"effective":[12,48],"way":[13],"to":[14,39,46,80,97],"help":[15],"people":[16],"deal":[17],"with":[18,125],"information":[19],"overload.":[20],"Recent":[21],"research":[22],"has":[23],"identified":[24],"significant":[25],"vulnerabilities":[26],"collaborative":[28,51],"techniques.":[30],"Shilling":[31],"attacks,":[32],"which":[34],"attackers":[35],"introduce":[36],"biased":[37],"ratings":[38],"influence":[40],"recommendation":[41],"systems,":[42],"been":[44],"shown":[45],"be":[47],"against":[49],"memory-based":[50,101],"algorithms.":[53,102],"We":[54],"examine":[55],"effectiveness":[57],"of":[58],"two":[59],"shilling":[61,98,123],"attacks":[62,99,124],"(the":[63],"random":[64,122],"attack":[65,107],"and":[66,116,129],"average":[68],"attack)":[69],"on":[70,112],"a":[71,82],"model-based":[72],"algorithm":[73,92,115],"that":[74,89,118],"uses":[75],"Singular":[76],"Value":[77],"Decomposition":[78],"(SVD)":[79],"learn":[81],"low-dimensional":[83],"linear":[84],"model.":[85],"Our":[86],"results":[87],"show":[88,117],"SVD-based":[91,114],"is":[93],"much":[94],"more":[95],"resistant":[96],"than":[100],"Furthermore,":[103],"we":[104],"develop":[105],"detection":[108,127],"method":[109,120],"directly":[110],"built":[111],"this":[119],"detects":[121],"high":[126],"rates":[128],"very":[130],"low":[131],"false":[132],"alarm":[133],"rates.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}