{"id":"https://openalex.org/W4318147598","doi":"https://doi.org/10.1109/bigdata55660.2022.10020682","title":"FVec2vec: A Fast Nonlinear Dimensionality Reduction Approach for General Data","display_name":"FVec2vec: A Fast Nonlinear Dimensionality Reduction Approach for General Data","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W4318147598","doi":"https://doi.org/10.1109/bigdata55660.2022.10020682"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020682","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020682","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","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/A5112566457","display_name":"Xiaoli Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoli Ren","raw_affiliation_strings":["National University of Defense Technology,College of Meteorology and Oceanography,Changsha,China","College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Meteorology and Oceanography,Changsha,China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053341118","display_name":"Kefeng Deng","orcid":"https://orcid.org/0000-0003-0925-6937"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kefeng Deng","raw_affiliation_strings":["National University of Defense Technology,College of Meteorology and Oceanography,Changsha,China","College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Meteorology and Oceanography,Changsha,China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102374259","display_name":"Kaijun Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaijun Ren","raw_affiliation_strings":["National University of Defense Technology,College of Meteorology and Oceanography,Changsha,China","College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Meteorology and Oceanography,Changsha,China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101788380","display_name":"Junqiang Song","orcid":"https://orcid.org/0009-0003-2686-566X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junqiang Song","raw_affiliation_strings":["National University of Defense Technology,College of Meteorology and Oceanography,Changsha,China","College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Meteorology and Oceanography,Changsha,China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100673949","display_name":"Xiaoyong Li","orcid":"https://orcid.org/0000-0001-5597-9306"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyong Li","raw_affiliation_strings":["National University of Defense Technology,College of Meteorology and Oceanography,Changsha,China","College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Meteorology and Oceanography,Changsha,China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102295333","display_name":"Qing Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Xu","raw_affiliation_strings":["National University of Defense Technology,College of Meteorology and Oceanography,Changsha,China","College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Meteorology and Oceanography,Changsha,China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5112566457"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19668157,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":null,"first_page":"1350","last_page":"1355"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9991999864578247,"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/T10057","display_name":"Face and Expression Recognition","score":0.9965999722480774,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9890000224113464,"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/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.7334136366844177},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6982659697532654},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6393854022026062},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.5936437845230103},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5650135278701782},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.5261066555976868},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.5193973183631897},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49334731698036194},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4141072928905487},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4139323830604553},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.41047054529190063},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37740039825439453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37480077147483826},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3746398687362671},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.28844302892684937}],"concepts":[{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.7334136366844177},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6982659697532654},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6393854022026062},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.5936437845230103},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5650135278701782},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.5261066555976868},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.5193973183631897},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49334731698036194},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4141072928905487},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4139323830604553},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.41047054529190063},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37740039825439453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37480077147483826},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3746398687362671},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28844302892684937},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata55660.2022.10020682","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020682","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.7400000095367432,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1502916507","https://openalex.org/W1614298861","https://openalex.org/W1888005072","https://openalex.org/W1993436046","https://openalex.org/W2001141328","https://openalex.org/W2053186076","https://openalex.org/W2099253838","https://openalex.org/W2110026675","https://openalex.org/W2154851992","https://openalex.org/W2156718197","https://openalex.org/W2187089797","https://openalex.org/W2294798173","https://openalex.org/W2786672974","https://openalex.org/W2888634710","https://openalex.org/W2889326414","https://openalex.org/W2951527381","https://openalex.org/W2954691982","https://openalex.org/W2962756421","https://openalex.org/W2989747508","https://openalex.org/W2997348928","https://openalex.org/W3014040695","https://openalex.org/W3104097132","https://openalex.org/W3158322187","https://openalex.org/W4288098430","https://openalex.org/W6629956336","https://openalex.org/W6636510571","https://openalex.org/W6768378539","https://openalex.org/W6772327032"],"related_works":["https://openalex.org/W2375574759","https://openalex.org/W2383239174","https://openalex.org/W3088634662","https://openalex.org/W117517268","https://openalex.org/W3162910294","https://openalex.org/W2539700568","https://openalex.org/W1996633793","https://openalex.org/W2931531042","https://openalex.org/W1489327846","https://openalex.org/W2364156185"],"abstract_inverted_index":{"Dimensionality":[0],"reduction":[1,77],"is":[2,149,162],"a":[3,72,127],"fundamental":[4],"technique":[5],"to":[6,56,86,131,137],"address":[7],"the":[8,35,40,58,61,83,108,135,139,142,160,166],"curse":[9],"of":[10,39,50,60,89,95,112,141],"dimensionality":[11,76],"problem":[12],"in":[13,116],"real-world":[14],"big":[15],"datasets.":[16],"However,":[17],"most":[18,152],"existing":[19,153],"methods":[20,154],"either":[21],"only":[22],"target":[23],"raw":[24],"datasets":[25],"that":[26,147],"contain":[27],"explicit":[28],"relationships":[29],"between":[30,103],"data":[31,51,104,114],"points,":[32,105],"or":[33],"construct":[34],"complete":[36],"neighborhood":[37,97],"graph":[38,98],"dataset":[41],"by":[42,53,99,118],"calculating":[43,100],"pairwise":[44,101],"similarities,":[45],"and":[46,159],"then":[47],"generate":[48],"contexts":[49],"points":[52],"random":[54],"walking":[55],"measure":[57],"structure":[59,140],"dataset,":[62],"which":[63,81],"are":[64],"computationally":[65],"expensive.":[66],"In":[67],"this":[68],"paper,":[69],"we":[70,106,125],"propose":[71],"fast":[73],"nonlinear":[74],"locality-preserving":[75],"approach":[78],"called":[79],"FVec2vec,":[80],"extends":[82],"Skip-gram":[84],"model":[85],"embedding":[87],"representation":[88],"general":[90],"numerical":[91],"matrices.":[92],"Specifically,":[93],"instead":[94],"constructing":[96],"similarities":[102],"approximate":[107],"k-nearest":[109],"neighbors":[110,122],"(kNN)":[111],"each":[113],"point":[115],"matrices":[117],"exploring":[119],"its":[120],"neighbors\u2019":[121],"first.":[123],"Then,":[124],"design":[126],"novel":[128],"sampling":[129],"algorithm":[130],"randomly":[132],"sample":[133],"on":[134],"kNN":[136],"depict":[138],"dataset.":[143],"Experimental":[144],"results":[145],"show":[146],"FVec2vec":[148],"faster":[150],"than":[151,165],"while":[155],"achieving":[156],"acceptable":[157],"accuracy,":[158],"accuracy":[161],"even":[163],"higher":[164],"state-of-the-art":[167],"method":[168],"under":[169],"certain":[170],"similarity":[171],"metrics.":[172]},"counts_by_year":[],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}
