{"id":"https://openalex.org/W2544145541","doi":"https://doi.org/10.1109/dsaa.2014.7058051","title":"Semi-randomized hashing for large scale data retrieval","display_name":"Semi-randomized hashing for large scale data retrieval","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2544145541","doi":"https://doi.org/10.1109/dsaa.2014.7058051","mag":"2544145541"},"language":"en","primary_location":{"id":"doi:10.1109/dsaa.2014.7058051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa.2014.7058051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10072/67949","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069376593","display_name":"Haichuan Yang","orcid":"https://orcid.org/0000-0001-7100-7945"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haichuan Yang","raw_affiliation_strings":["School of Computer Since and Engineering, Beihang University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Since and Engineering, Beihang University, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101790836","display_name":"Xiao Bai","orcid":"https://orcid.org/0000-0001-8561-9299"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Bai","raw_affiliation_strings":["School of Computer Since and Engineering, Beihang University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Since and Engineering, Beihang University, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100781212","display_name":"Jun Zhou","orcid":"https://orcid.org/0000-0001-5822-8233"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jun Zhou","raw_affiliation_strings":["School of Information and Communication Technology, Griffith University, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Technology, Griffith University, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100767701","display_name":"Peng Ren","orcid":"https://orcid.org/0000-0001-9506-5875"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Ren","raw_affiliation_strings":["College of Information and Control Engineering China University of Petroleum, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Control Engineering China University of Petroleum, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112149353","display_name":"Jian Cheng","orcid":"https://orcid.org/0000-0003-1289-2758"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Cheng","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017499714","display_name":"Lu Bai","orcid":"https://orcid.org/0000-0003-1242-5412"},"institutions":[{"id":"https://openalex.org/I52099693","display_name":"University of York","ror":"https://ror.org/04m01e293","country_code":"GB","type":"education","lineage":["https://openalex.org/I52099693"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lu Bai","raw_affiliation_strings":["Department of Computer Science, University of York, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of York, UK","institution_ids":["https://openalex.org/I52099693"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"53","last_page":"58"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T11478","display_name":"Caching and Content Delivery","score":0.9758999943733215,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.9711999893188477,"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/k-independent-hashing","display_name":"K-independent hashing","score":0.8099749088287354},{"id":"https://openalex.org/keywords/dynamic-perfect-hashing","display_name":"Dynamic perfect hashing","score":0.7657887935638428},{"id":"https://openalex.org/keywords/random-projection","display_name":"Random projection","score":0.720633864402771},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.6664566993713379},{"id":"https://openalex.org/keywords/universal-hashing","display_name":"Universal hashing","score":0.6551401615142822},{"id":"https://openalex.org/keywords/locality-sensitive-hashing","display_name":"Locality-sensitive hashing","score":0.6427136659622192},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.6258459687232971},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5842466354370117},{"id":"https://openalex.org/keywords/feature-hashing","display_name":"Feature hashing","score":0.5766711831092834},{"id":"https://openalex.org/keywords/linear-hashing","display_name":"Linear hashing","score":0.572161853313446},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.47014477849006653},{"id":"https://openalex.org/keywords/double-hashing","display_name":"Double hashing","score":0.42799943685531616},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3717792332172394},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.31065189838409424},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2703705430030823}],"concepts":[{"id":"https://openalex.org/C187062812","wikidata":"https://www.wikidata.org/wiki/Q6322840","display_name":"K-independent hashing","level":5,"score":0.8099749088287354},{"id":"https://openalex.org/C122907437","wikidata":"https://www.wikidata.org/wiki/Q5318999","display_name":"Dynamic perfect hashing","level":5,"score":0.7657887935638428},{"id":"https://openalex.org/C2777036070","wikidata":"https://www.wikidata.org/wiki/Q18393452","display_name":"Random projection","level":2,"score":0.720633864402771},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.6664566993713379},{"id":"https://openalex.org/C116058348","wikidata":"https://www.wikidata.org/wiki/Q846912","display_name":"Universal hashing","level":5,"score":0.6551401615142822},{"id":"https://openalex.org/C74270461","wikidata":"https://www.wikidata.org/wiki/Q1625299","display_name":"Locality-sensitive hashing","level":4,"score":0.6427136659622192},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.6258459687232971},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5842466354370117},{"id":"https://openalex.org/C133667856","wikidata":"https://www.wikidata.org/wiki/Q5439682","display_name":"Feature hashing","level":5,"score":0.5766711831092834},{"id":"https://openalex.org/C36375716","wikidata":"https://www.wikidata.org/wiki/Q6553456","display_name":"Linear hashing","level":5,"score":0.572161853313446},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.47014477849006653},{"id":"https://openalex.org/C138111711","wikidata":"https://www.wikidata.org/wiki/Q478351","display_name":"Double hashing","level":4,"score":0.42799943685531616},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3717792332172394},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31065189838409424},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2703705430030823},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/dsaa.2014.7058051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa.2014.7058051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/67949","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/67949","pdf_url":"http://hdl.handle.net/10072/67949","source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.718.8803","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.718.8803","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ict.griffith.edu.au/%7Ejunzhou/papers/C_DSAA_2014.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.829.7471","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.829.7471","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www98.griffith.edu.au/dspace/bitstream/handle/10072/67949/99226_1.pdf%3Bjsessionid%3D30C24DFA78E0AFFB37837801F5F42202?sequence%3D1","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:research-repository.griffith.edu.au:10072/67949","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/67949","pdf_url":"http://hdl.handle.net/10072/67949","source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2544145541.pdf","grobid_xml":"https://content.openalex.org/works/W2544145541.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W118147013","https://openalex.org/W1564609383","https://openalex.org/W1566135517","https://openalex.org/W1883985887","https://openalex.org/W1972036246","https://openalex.org/W1974647172","https://openalex.org/W1990537115","https://openalex.org/W1994389483","https://openalex.org/W2012592962","https://openalex.org/W2012833704","https://openalex.org/W2045533739","https://openalex.org/W2055906546","https://openalex.org/W2057069782","https://openalex.org/W2061681393","https://openalex.org/W2085922539","https://openalex.org/W2122929038","https://openalex.org/W2124509324","https://openalex.org/W2125378448","https://openalex.org/W2147717514","https://openalex.org/W2162006472","https://openalex.org/W2168467811","https://openalex.org/W2292992741","https://openalex.org/W2293597654","https://openalex.org/W2294155285","https://openalex.org/W2408177717","https://openalex.org/W3118608800","https://openalex.org/W4205637966","https://openalex.org/W4230940751","https://openalex.org/W4252200713","https://openalex.org/W6678556256","https://openalex.org/W6696680836","https://openalex.org/W6696891034","https://openalex.org/W6697214482","https://openalex.org/W6714263872","https://openalex.org/W6787972765","https://openalex.org/W6834473044"],"related_works":["https://openalex.org/W2023326318","https://openalex.org/W2811247857","https://openalex.org/W2893252848","https://openalex.org/W1554555624","https://openalex.org/W2783286101","https://openalex.org/W2544145541","https://openalex.org/W2100189723","https://openalex.org/W2962766560","https://openalex.org/W1969241115","https://openalex.org/W2151368806"],"abstract_inverted_index":{"In":[0,35,104],"information":[1],"retrieval,":[2],"efficient":[3],"accomplishing":[4],"the":[5,31,46,79,105,110,119,131,140,169,176],"nearest":[6,33],"neighbor":[7],"search":[8],"on":[9,78,175],"large":[10,177],"scale":[11,178],"database":[12],"is":[13,55,155],"a":[14,26,40,56,100],"great":[15],"challenge.":[16],"Hashing":[17],"based":[18],"indexing":[19],"methods":[20,64,172],"represent":[21],"each":[22],"data":[23,141],"instance":[24],"as":[25],"binary":[27,50,125],"string":[28],"to":[29,44,72,113],"retrieve":[30],"approximate":[32],"neighbors.":[34],"this":[36,74],"paper,":[37],"we":[38],"present":[39],"semi-randomized":[41],"hashing":[42,63,160],"approach":[43,167],"preserve":[45],"Euclidean":[47,52],"distance":[48,53],"by":[49,99],"codes.":[51,126],"preserving":[54],"classic":[57],"research":[58],"problem":[59,132],"in":[60,157],"hashing.":[61],"Most":[62],"used":[65],"purely":[66],"randomized":[67,84,134],"or":[68],"optimized":[69,86],"learning":[70],"strategy":[71],"achieve":[73],"goal.":[75],"Our":[76],"method,":[77],"other":[80],"hand,":[81],"combines":[82],"both":[83],"and":[85,95,124],"strategies.":[87],"It":[88],"starts":[89],"from":[90,139],"generating":[91],"multiple":[92],"random":[93],"vectors,":[94],"then":[96],"approximates":[97],"them":[98],"single":[101],"projection":[102],"vector.":[103],"quantization":[106],"step,":[107],"it":[108],"uses":[109],"orthogonal":[111],"transformation":[112],"minimize":[114],"an":[115,148],"upper":[116],"bound":[117],"of":[118,151],"deviation":[120],"between":[121],"real-valued":[122],"vectors":[123],"The":[127,162],"proposed":[128],"method":[129,146],"overcomes":[130],"that":[133,165],"hash":[135,152],"functions":[136],"are":[137],"isolated":[138],"distribution.":[142],"What's":[143],"more,":[144],"our":[145,166],"supports":[147],"arbitrary":[149],"number":[150],"functions,":[153],"which":[154],"beneficial":[156],"building":[158],"better":[159],"methods.":[161],"experiments":[163],"show":[164],"outperforms":[168],"alternative":[170],"state-of-the-art":[171],"for":[173],"retrieval":[174],"dataset.":[179]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
