{"id":"https://openalex.org/W2604433096","doi":"https://doi.org/10.1145/3038912.3052639","title":"Collaborative Metric Learning","display_name":"Collaborative Metric Learning","publication_year":2017,"publication_date":"2017-04-03","ids":{"openalex":"https://openalex.org/W2604433096","doi":"https://doi.org/10.1145/3038912.3052639","mag":"2604433096"},"language":"en","primary_location":{"id":"doi:10.1145/3038912.3052639","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3038912.3052639","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 26th International Conference on World Wide Web","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3038912.3052639","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039275573","display_name":"Cheng-Kang Hsieh","orcid":null},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cheng-Kang Hsieh","raw_affiliation_strings":["University of California, Los Angeles, Los Angeles, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057330200","display_name":"Longqi Yang","orcid":"https://orcid.org/0000-0002-6615-8615"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]},{"id":"https://openalex.org/I4405261073","display_name":"Cornell Tech","ror":"https://ror.org/04qscbg47","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Longqi Yang","raw_affiliation_strings":["Cornell Tech, New York City, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell Tech, New York City, NY, USA","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041864624","display_name":"Yin Cui","orcid":"https://orcid.org/0000-0003-0070-5118"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]},{"id":"https://openalex.org/I4405261073","display_name":"Cornell Tech","ror":"https://ror.org/04qscbg47","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yin Cui","raw_affiliation_strings":["Cornell Tech, New York City, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell Tech, New York City, NY, USA","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052768778","display_name":"Tsung-Yi Lin","orcid":"https://orcid.org/0000-0003-4819-0627"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]},{"id":"https://openalex.org/I4405261073","display_name":"Cornell Tech","ror":"https://ror.org/04qscbg47","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tsung-Yi Lin","raw_affiliation_strings":["Cornell Tech, New York City, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell Tech, New York City, NY, USA","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018609918","display_name":"Serge Belongie","orcid":"https://orcid.org/0000-0002-0388-5217"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]},{"id":"https://openalex.org/I4405261073","display_name":"Cornell Tech","ror":"https://ror.org/04qscbg47","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Serge Belongie","raw_affiliation_strings":["Cornell Tech, New York City, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell Tech, New York City, NY, USA","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051587086","display_name":"Deborah Estrin","orcid":"https://orcid.org/0000-0001-6477-0096"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]},{"id":"https://openalex.org/I4405261073","display_name":"Cornell Tech","ror":"https://ror.org/04qscbg47","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deborah Estrin","raw_affiliation_strings":["Cornell Tech, New York City, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell Tech, New York City, NY, USA","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":553,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"193","last_page":"201"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9977999925613403,"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":0.9977999925613403,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9502000212669373,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9093000292778015,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/collaborative-filtering","display_name":"Collaborative filtering","score":0.7833483815193176},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7825375199317932},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.7592710852622986},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6382761597633362},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6288853883743286},{"id":"https://openalex.org/keywords/metric-space","display_name":"Metric space","score":0.6002558469772339},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5778024792671204},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5667520761489868},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.5095605850219727},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42628753185272217},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4175671935081482},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.41042742133140564},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37774553894996643},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3353155851364136},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3251607120037079},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10450828075408936}],"concepts":[{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.7833483815193176},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7825375199317932},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7592710852622986},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6382761597633362},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6288853883743286},{"id":"https://openalex.org/C198043062","wikidata":"https://www.wikidata.org/wiki/Q180953","display_name":"Metric space","level":2,"score":0.6002558469772339},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5778024792671204},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5667520761489868},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.5095605850219727},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42628753185272217},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4175671935081482},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.41042742133140564},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37774553894996643},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3353155851364136},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3251607120037079},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10450828075408936},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3038912.3052639","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3038912.3052639","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 26th International Conference on World Wide Web","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3038912.3052639","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3038912.3052639","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 26th International Conference on World Wide Web","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320318127","display_name":"UnitedHealth Group","ror":"https://ror.org/04a8rt780"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W227501432","https://openalex.org/W639274388","https://openalex.org/W1480376833","https://openalex.org/W1569512666","https://openalex.org/W1599364940","https://openalex.org/W1965355809","https://openalex.org/W1974627246","https://openalex.org/W2010416066","https://openalex.org/W2054141820","https://openalex.org/W2059993991","https://openalex.org/W2061503185","https://openalex.org/W2066611560","https://openalex.org/W2068042582","https://openalex.org/W2089349245","https://openalex.org/W2090679992","https://openalex.org/W2101409192","https://openalex.org/W2102765684","https://openalex.org/W2106053110","https://openalex.org/W2108630796","https://openalex.org/W2111138053","https://openalex.org/W2111286903","https://openalex.org/W2113479237","https://openalex.org/W2117154949","https://openalex.org/W2121949863","https://openalex.org/W2123229215","https://openalex.org/W2124187902","https://openalex.org/W2135505871","https://openalex.org/W2135790056","https://openalex.org/W2140310134","https://openalex.org/W2140376886","https://openalex.org/W2145287260","https://openalex.org/W2146502635","https://openalex.org/W2148781362","https://openalex.org/W2152314154","https://openalex.org/W2155106456","https://openalex.org/W2155912844","https://openalex.org/W2157364932","https://openalex.org/W2157881433","https://openalex.org/W2158978451","https://openalex.org/W2159094788","https://openalex.org/W2169054943","https://openalex.org/W2181083374","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2219193941","https://openalex.org/W2219888463","https://openalex.org/W2295739661","https://openalex.org/W2338177254","https://openalex.org/W2384495648","https://openalex.org/W2557283755","https://openalex.org/W2962917313","https://openalex.org/W2963655167","https://openalex.org/W2998508934","https://openalex.org/W4210880854","https://openalex.org/W4403221500","https://openalex.org/W6676794045","https://openalex.org/W6680832709"],"related_works":["https://openalex.org/W2148008870","https://openalex.org/W2381195555","https://openalex.org/W2368606575","https://openalex.org/W4246757943","https://openalex.org/W2085998272","https://openalex.org/W2369874856","https://openalex.org/W2182477562","https://openalex.org/W2792185758","https://openalex.org/W2787484455","https://openalex.org/W2119808169"],"abstract_inverted_index":{"Metric":[0,29],"learning":[1,22],"algorithms":[2,58],"produce":[3],"distance":[4],"metrics":[5],"that":[6],"capture":[7],"the":[8,18,46,68],"important":[9],"relationships":[10],"among":[11],"data.":[12],"In":[13],"this":[14],"work,":[15],"we":[16],"study":[17],"connection":[19],"between":[20],"metric":[21,36],"and":[23,48,66],"collaborative":[24,56],"filtering.":[25],"We":[26],"propose":[27],"Collaborative":[28],"Learning":[30],"(CML)":[31],"which":[32],"learns":[33],"a":[34,60],"joint":[35],"space":[37],"to":[38],"encode":[39],"not":[40],"only":[41],"users'":[42,72],"preferences":[43],"but":[44],"also":[45,76],"user-user":[47],"item-item":[49],"similarity.":[50],"The":[51],"proposed":[52],"algorithm":[53],"outperforms":[54],"state-of-the-art":[55],"filtering":[57],"on":[59],"wide":[61],"range":[62],"of":[63,71],"recommendation":[64,82],"tasks":[65,83],"uncovers":[67],"underlying":[69],"spectrum":[70],"fine-grained":[73],"preferences.":[74],"CML":[75],"achieves":[77],"significant":[78],"speedup":[79],"for":[80],"Top-K":[81],"using":[84],"off-the-shelf,":[85],"approximate":[86],"nearest-neighbor":[87],"search,":[88],"with":[89],"negligible":[90],"accuracy":[91],"reduction.":[92]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":43},{"year":2023,"cited_by_count":63},{"year":2022,"cited_by_count":79},{"year":2021,"cited_by_count":107},{"year":2020,"cited_by_count":80},{"year":2019,"cited_by_count":85},{"year":2018,"cited_by_count":48},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-10T00:00:00"}
