{"id":"https://openalex.org/W1996936615","doi":"https://doi.org/10.1145/2600428.2609600","title":"Supervised hashing with latent factor models","display_name":"Supervised hashing with latent factor models","publication_year":2014,"publication_date":"2014-07-03","ids":{"openalex":"https://openalex.org/W1996936615","doi":"https://doi.org/10.1145/2600428.2609600","mag":"1996936615"},"language":"en","primary_location":{"id":"doi:10.1145/2600428.2609600","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2600428.2609600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval","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/A5058628803","display_name":"Peichao Zhang","orcid":"https://orcid.org/0000-0003-1546-1021"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peichao Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China","[Shanghai Jiao Tong University, Shanghai, China]"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"[Shanghai Jiao Tong University, Shanghai, China]","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101541045","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0001-6763-8146"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China","[Shanghai Jiao Tong University, Shanghai, China]"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"[Shanghai Jiao Tong University, Shanghai, China]","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101402002","display_name":"Wu-Jun Li","orcid":"https://orcid.org/0000-0003-2499-4006"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wu-Jun Li","raw_affiliation_strings":["Nanjing University, Nanjing , China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing , China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039318240","display_name":"Minyi Guo","orcid":"https://orcid.org/0000-0003-0034-2302"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minyi Guo","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai , China","[Shanghai Jiao Tong University, Shanghai, China]"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai , China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"[Shanghai Jiao Tong University, Shanghai, China]","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5058628803"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":16.5833,"has_fulltext":false,"cited_by_count":290,"citation_normalized_percentile":{"value":0.99382154,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"173","last_page":"182"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":1.0,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9948999881744385,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9886999726295471,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7116258144378662},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.7001018524169922},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5767154097557068},{"id":"https://openalex.org/keywords/binary-code","display_name":"Binary code","score":0.5133668780326843},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48131096363067627},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.4474237561225891},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4402518570423126},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.42947983741760254},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.3834252953529358},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34268301725387573},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33826112747192383},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21943092346191406}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7116258144378662},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.7001018524169922},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5767154097557068},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.5133668780326843},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48131096363067627},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.4474237561225891},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4402518570423126},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.42947983741760254},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.3834252953529358},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34268301725387573},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33826112747192383},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21943092346191406},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2600428.2609600","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2600428.2609600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1552395088","display_name":null,"funder_award_id":"61100125","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2211159950","display_name":null,"funder_award_id":"2012AA011003","funder_id":"https://openalex.org/F4320321540","funder_display_name":"Ministry of Science and Technology of the People's Republic of China"},{"id":"https://openalex.org/G372256174","display_name":null,"funder_award_id":"13511504200","funder_id":"https://openalex.org/F4320321885","funder_display_name":"Science and Technology Commission of Shanghai Municipality"},{"id":"https://openalex.org/G4005836112","display_name":null,"funder_award_id":"61261160502","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4166410561","display_name":null,"funder_award_id":"61272099","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321540","display_name":"Ministry of Science and Technology of the People's Republic of China","ror":"https://ror.org/027s68j25"},{"id":"https://openalex.org/F4320321885","display_name":"Science and Technology Commission of Shanghai Municipality","ror":"https://ror.org/03kt66j61"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W1489843519","https://openalex.org/W1502916507","https://openalex.org/W1835419070","https://openalex.org/W1981053739","https://openalex.org/W1992371516","https://openalex.org/W2007972815","https://openalex.org/W2015175493","https://openalex.org/W2019076926","https://openalex.org/W2023236957","https://openalex.org/W2031637148","https://openalex.org/W2039284087","https://openalex.org/W2044195942","https://openalex.org/W2049993534","https://openalex.org/W2061441693","https://openalex.org/W2064797228","https://openalex.org/W2084363474","https://openalex.org/W2113307832","https://openalex.org/W2121713321","https://openalex.org/W2122205543","https://openalex.org/W2125378448","https://openalex.org/W2130660124","https://openalex.org/W2134514757","https://openalex.org/W2144892774","https://openalex.org/W2145065594","https://openalex.org/W2145607950","https://openalex.org/W2147717514","https://openalex.org/W2154956324","https://openalex.org/W2162006472","https://openalex.org/W2162666105","https://openalex.org/W2162670057","https://openalex.org/W2164338181","https://openalex.org/W2171790913","https://openalex.org/W2203543769","https://openalex.org/W2221852422","https://openalex.org/W2251864938","https://openalex.org/W2255038316","https://openalex.org/W2293597654","https://openalex.org/W2294155285","https://openalex.org/W2397770138","https://openalex.org/W2408177717","https://openalex.org/W2427881153","https://openalex.org/W2602753196","https://openalex.org/W2912584497","https://openalex.org/W2913932916","https://openalex.org/W3118608800","https://openalex.org/W4245550249","https://openalex.org/W6629956336","https://openalex.org/W6648560114","https://openalex.org/W6676931166","https://openalex.org/W6678246256","https://openalex.org/W6684115544","https://openalex.org/W6684181414","https://openalex.org/W6688844344","https://openalex.org/W6691474080","https://openalex.org/W6696680836","https://openalex.org/W6697214482","https://openalex.org/W6714263872","https://openalex.org/W6758894599"],"related_works":["https://openalex.org/W2134880816","https://openalex.org/W2111298487","https://openalex.org/W2088296667","https://openalex.org/W2963758661","https://openalex.org/W2055498716","https://openalex.org/W4386075138","https://openalex.org/W1984130439","https://openalex.org/W3016499519","https://openalex.org/W2371359060","https://openalex.org/W2562873141"],"abstract_inverted_index":{"Due":[0],"to":[1,27,54,89,106],"its":[2],"low":[3],"storage":[4],"cost":[5],"and":[6],"fast":[7],"query":[8],"speed,":[9],"hashing":[10,24,50,83],"has":[11],"been":[12],"widely":[13],"adopted":[14],"for":[15,121],"approximate":[16],"nearest":[17],"neighbor":[18],"search":[19],"in":[20,32],"large-scale":[21,125],"datasets.":[22,126],"Traditional":[23],"methods":[25,145],"try":[26,53],"learn":[28,90,107],"the":[29,37,42,56,61,65,108],"hash":[30],"codes":[31,93],"an":[33],"unsupervised":[34,73],"way":[35],"where":[36],"metric":[38],"(Euclidean)":[39],"structure":[40,58],"of":[41,64,110],"training":[43,66,122,148],"data":[44],"is":[45,104,119],"preserved.":[46],"Very":[47],"recently,":[48],"supervised":[49,82],"methods,":[51],"which":[52],"preserve":[55],"semantic":[57,62,134],"constructed":[59],"from":[60],"labels":[63,135],"points,":[67],"have":[68],"exhibited":[69],"higher":[70],"accuracy":[71,142],"than":[72,143],"methods.":[74],"In":[75],"this":[76],"paper,":[77],"we":[78],"propose":[79],"a":[80,113],"novel":[81],"method,":[84],"called":[85],"latent":[86,96],"factor":[87,97],"hashing(LFH),":[88],"similarity-preserving":[91],"binary":[92],"based":[94],"on":[95,124,129],"models.":[98],"An":[99],"algorithm":[100],"with":[101,116,133,146],"convergence":[102],"guarantee":[103],"proposed":[105,120],"parameters":[109],"LFH.":[111],"Furthermore,":[112],"linear-time":[114],"variant":[115],"stochastic":[117],"learning":[118],"LFH":[123,138],"Experimental":[127],"results":[128],"two":[130],"large":[131],"datasets":[132],"show":[136],"that":[137],"can":[139],"achieve":[140],"superior":[141],"state-of-the-art":[144],"comparable":[147],"time.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":21},{"year":2021,"cited_by_count":32},{"year":2020,"cited_by_count":43},{"year":2019,"cited_by_count":51},{"year":2018,"cited_by_count":45},{"year":2017,"cited_by_count":44},{"year":2016,"cited_by_count":17},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}