{"id":"https://openalex.org/W4212928951","doi":"https://doi.org/10.1109/tkde.2022.3151474","title":"Network Representation Lightening from Hashing to Quantization","display_name":"Network Representation Lightening from Hashing to Quantization","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4212928951","doi":"https://doi.org/10.1109/tkde.2022.3151474"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2022.3151474","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3151474","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5085254654","display_name":"Defu Lian","orcid":"https://orcid.org/0000-0002-3507-9607"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Defu Lian","raw_affiliation_strings":["School of Computer Science and Technology, University of Science and Technology of China, 12652 Hefei, Anhui, China, 230026"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, University of Science and Technology of China, 12652 Hefei, Anhui, China, 230026","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048511473","display_name":"Zhihao Zhu","orcid":"https://orcid.org/0000-0001-5814-1939"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihao Zhu","raw_affiliation_strings":["School of Data Science, University of Science and Technology of China, 12652 Hefei, Anhui, China,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science, University of Science and Technology of China, 12652 Hefei, Anhui, China,","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100603979","display_name":"Kai Zheng","orcid":"https://orcid.org/0000-0002-0217-3998"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Zheng","raw_affiliation_strings":["Computer Science, University of Electronic Science and Technology of China, 12599 Chengdu, Sichuan, China,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science, University of Electronic Science and Technology of China, 12599 Chengdu, Sichuan, China,","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101744165","display_name":"Yong Ge","orcid":"https://orcid.org/0000-0001-8094-4180"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yong Ge","raw_affiliation_strings":["Eller College of Management, University of Arizona, 8041 Tucson, Arizona, United States,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eller College of Management, University of Arizona, 8041 Tucson, Arizona, United States,","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044651577","display_name":"Xing Xie","orcid":"https://orcid.org/0000-0002-8608-8482"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Xie","raw_affiliation_strings":["Web Search and Mining Group, Microsoft Research Asia, Beijing, Beijing, China, 100190"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Web Search and Mining Group, Microsoft Research Asia, Beijing, Beijing, China, 100190","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048237545","display_name":"Enhong Chen","orcid":"https://orcid.org/0000-0002-4835-4102"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Enhong Chen","raw_affiliation_strings":["School of Computer Science, University of Science and Technology of China, Hefei, Anhui, China,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Science and Technology of China, Hefei, Anhui, China,","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3936,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.64609047,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994000196456909,"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":0.9994000196456909,"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/T11478","display_name":"Caching and Content Delivery","score":0.9933000206947327,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7347458004951477},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5638214945793152},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.5173870325088501},{"id":"https://openalex.org/keywords/pagerank","display_name":"PageRank","score":0.49524059891700745},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4806210398674011},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.44710004329681396},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4355061948299408},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.42211538553237915},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.37543609738349915},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30656537413597107},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24017730355262756}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7347458004951477},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5638214945793152},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.5173870325088501},{"id":"https://openalex.org/C2779172887","wikidata":"https://www.wikidata.org/wiki/Q184316","display_name":"PageRank","level":2,"score":0.49524059891700745},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4806210398674011},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.44710004329681396},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4355061948299408},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.42211538553237915},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.37543609738349915},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30656537413597107},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24017730355262756},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2022.3151474","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3151474","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3179083445","display_name":null,"funder_award_id":"62022077","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4799459813","display_name":null,"funder_award_id":"61976198","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W288635123","https://openalex.org/W391578156","https://openalex.org/W1888005072","https://openalex.org/W1910300841","https://openalex.org/W1974647172","https://openalex.org/W1977182282","https://openalex.org/W1999032440","https://openalex.org/W2046253692","https://openalex.org/W2062388999","https://openalex.org/W2077815765","https://openalex.org/W2090891622","https://openalex.org/W2101409192","https://openalex.org/W2107569009","https://openalex.org/W2119913432","https://openalex.org/W2122196799","https://openalex.org/W2124509324","https://openalex.org/W2142535891","https://openalex.org/W2154851992","https://openalex.org/W2171572695","https://openalex.org/W2171700594","https://openalex.org/W2304387544","https://openalex.org/W2319920447","https://openalex.org/W2336920772","https://openalex.org/W2387462954","https://openalex.org/W2411707397","https://openalex.org/W2604298190","https://openalex.org/W2605182906","https://openalex.org/W2725001169","https://openalex.org/W2742528903","https://openalex.org/W2809280072","https://openalex.org/W2913932916","https://openalex.org/W2914833637","https://openalex.org/W2962756421","https://openalex.org/W2962975498","https://openalex.org/W2963224980","https://openalex.org/W2964015378","https://openalex.org/W2983848182","https://openalex.org/W2999664153","https://openalex.org/W3019716989","https://openalex.org/W3103311102","https://openalex.org/W3104097132","https://openalex.org/W3155986400","https://openalex.org/W3162616539","https://openalex.org/W4254197176","https://openalex.org/W4291474301","https://openalex.org/W6605707561","https://openalex.org/W6610514318","https://openalex.org/W6638721287","https://openalex.org/W6681077227","https://openalex.org/W6684295950","https://openalex.org/W6691474080","https://openalex.org/W6696680836","https://openalex.org/W6697214482","https://openalex.org/W6697873463","https://openalex.org/W6700264148","https://openalex.org/W6712733126","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6740103103"],"related_works":["https://openalex.org/W2127243424","https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W2972997031","https://openalex.org/W2075222291"],"abstract_inverted_index":{"Information":[0],"network":[1,171],"embedding":[2,121],"is":[3,97,107],"an":[4,148],"important":[5],"way":[6],"to":[7,57,86,139,175],"enable":[8],"efficient":[9,153],"graph":[10,65],"analytics.":[11],"However,":[12],"it":[13],"still":[14],"faces":[15],"with":[16,29,123,173],"computational":[17],"challenges":[18],"in":[19,193],"problems":[20,45],"such":[21],"as":[22],"link":[23],"prediction":[24],"and":[25,37,80,142,181,196],"node":[26,96,179,182],"recommendation,":[27],"particularly":[28],"the":[30,51,158,176],"increasing":[31],"scale":[32],"of":[33,48,105,178],"networks.":[34,92],"Both":[35],"hashing":[36],"quantization":[38],"are":[39],"promising":[40],"approaches":[41],"for":[42,61,90,152,157],"accelerating":[43],"these":[44],"by":[46,99],"orders":[47],"magnitude.":[49],"In":[50,93],"preliminary":[52],"work,":[53],"we":[54,83,127],"have":[55],"proposed":[56],"learn":[58,87,140],"binary":[59,141],"codes":[60,89],"information":[62,75,91,170,204],"networks,":[63],"but":[64],"analytics":[66],"may":[67],"suffer":[68],"from":[69,110],"large":[70],"accuracy":[71],"degradation.":[72],"To":[73],"reduce":[74],"loss":[76,205],"while":[77],"achieving":[78],"memory":[79],"search":[81],"efficiency,":[82],"further":[84],"propose":[85,128,147],"quantized":[88,143,198],"particular,":[94],"each":[95,104],"represented":[98],"compositing":[100],"multiple":[101],"latent":[102],"vectors,":[103],"which":[106],"optimally":[108],"selected":[109],"a":[111,129],"distinct":[112],"set.":[113],"Since":[114],"(generalized)":[115],"matrix":[116,160],"factorization":[117,161],"unifies":[118],"several":[119],"well-known":[120],"methods":[122],"high-order":[124],"proximity":[125],"preserved,":[126],"\\underline{N}etwork":[130],"\\underline{R}epresentation":[131],"\\underline{L}ightening":[132],"framework":[133],"based":[134],"on":[135,167],"\\underline{M}atrix":[136],"\\underline{F}actorization":[137],"(NRL-MF)":[138],"codes.":[144,208],"We":[145,163],"also":[146],"alternating":[149],"optimization":[150],"algorithm":[151],"parameter":[154],"learning,":[155],"even":[156],"generalized":[159],"case.":[162],"finally":[164],"evaluate":[165],"NRL-MF":[166,188],"four":[168],"real-world":[169],"datasets":[172],"respect":[174],"tasks":[177],"classification":[180],"recommendation.":[183],"The":[184],"results":[185],"show":[186],"that":[187,197],"significantly":[189],"outperforms":[190],"competing":[191],"baselines":[192],"both":[194],"tasks,":[195],"representations":[199],"indeed":[200],"incur":[201],"much":[202],"smaller":[203],"than":[206],"binarized":[207]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}