{"id":"https://openalex.org/W3137717089","doi":"https://doi.org/10.1109/bigdata50022.2020.9377854","title":"Large-scale Sparse Structural Node Representation","display_name":"Large-scale Sparse Structural Node Representation","publication_year":2020,"publication_date":"2020-12-10","ids":{"openalex":"https://openalex.org/W3137717089","doi":"https://doi.org/10.1109/bigdata50022.2020.9377854","mag":"3137717089"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata50022.2020.9377854","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9377854","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5009094578","display_name":"Edoardo Serra","orcid":"https://orcid.org/0000-0003-0689-5063"},"institutions":[{"id":"https://openalex.org/I120156002","display_name":"Boise State University","ror":"https://ror.org/02e3zdp86","country_code":"US","type":"education","lineage":["https://openalex.org/I120156002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Edoardo Serra","raw_affiliation_strings":["Computer Science Dept., Boise State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Dept., Boise State University","institution_ids":["https://openalex.org/I120156002"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025202119","display_name":"Mikel Joaristi","orcid":null},"institutions":[{"id":"https://openalex.org/I120156002","display_name":"Boise State University","ror":"https://ror.org/02e3zdp86","country_code":"US","type":"education","lineage":["https://openalex.org/I120156002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mikel Joaristi","raw_affiliation_strings":["Computer Science Dept., Boise State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Dept., Boise State University","institution_ids":["https://openalex.org/I120156002"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053225136","display_name":"Alfredo Cuzzocrea","orcid":"https://orcid.org/0000-0002-7104-6415"},"institutions":[{"id":"https://openalex.org/I45204951","display_name":"University of Calabria","ror":"https://ror.org/02rc97e94","country_code":"IT","type":"education","lineage":["https://openalex.org/I45204951"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alfredo Cuzzocrea","raw_affiliation_strings":["iDEA Lab, University of Calabria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"iDEA Lab, University of Calabria","institution_ids":["https://openalex.org/I45204951"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5247","last_page":"5253"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9685999751091003,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7861859798431396},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6778662204742432},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.600568413734436},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.592369556427002},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5649685263633728},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5461229085922241},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4864192008972168},{"id":"https://openalex.org/keywords/external-data-representation","display_name":"External Data Representation","score":0.46679598093032837},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4103900194168091},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39999473094940186},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2894393503665924}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7861859798431396},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6778662204742432},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.600568413734436},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.592369556427002},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5649685263633728},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5461229085922241},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4864192008972168},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.46679598093032837},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4103900194168091},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39999473094940186},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2894393503665924},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata50022.2020.9377854","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9377854","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarworks.boisestate.edu:cs_facpubs-1283","is_oa":false,"landing_page_url":"https://scholarworks.boisestate.edu/cs_facpubs/275","pdf_url":null,"source":{"id":"https://openalex.org/S4377196366","display_name":"Scholar Works  (Boise State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I120156002","host_organization_name":"Boise State University","host_organization_lineage":["https://openalex.org/I120156002"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computer Science Faculty Publications and Presentations","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W299861242","https://openalex.org/W1555148682","https://openalex.org/W1567365482","https://openalex.org/W1612884251","https://openalex.org/W1677991150","https://openalex.org/W1888005072","https://openalex.org/W2056132907","https://openalex.org/W2066043610","https://openalex.org/W2067889145","https://openalex.org/W2084626209","https://openalex.org/W2119821739","https://openalex.org/W2125736156","https://openalex.org/W2154851992","https://openalex.org/W2477497747","https://openalex.org/W2607500032","https://openalex.org/W2743469945","https://openalex.org/W2755088640","https://openalex.org/W2766537588","https://openalex.org/W2766954398","https://openalex.org/W2792234394","https://openalex.org/W2808409763","https://openalex.org/W2808867307","https://openalex.org/W2898213711","https://openalex.org/W2905224888","https://openalex.org/W2907492528","https://openalex.org/W2950256799","https://openalex.org/W2962756421","https://openalex.org/W2962767366","https://openalex.org/W2963512530","https://openalex.org/W2981151517","https://openalex.org/W3005939550","https://openalex.org/W3011415199","https://openalex.org/W3102794461","https://openalex.org/W3104097132","https://openalex.org/W3105705953","https://openalex.org/W4210257598","https://openalex.org/W4239510810","https://openalex.org/W4294558607","https://openalex.org/W6610601964","https://openalex.org/W6633204899","https://openalex.org/W6636339257","https://openalex.org/W6637311423","https://openalex.org/W6738964360","https://openalex.org/W6744271739","https://openalex.org/W6747581376","https://openalex.org/W6757374366","https://openalex.org/W6977528248"],"related_works":["https://openalex.org/W2952512863","https://openalex.org/W3134504629","https://openalex.org/W2938696877","https://openalex.org/W4323911413","https://openalex.org/W1982536061","https://openalex.org/W4210631502","https://openalex.org/W4286796787","https://openalex.org/W2952582877","https://openalex.org/W4361192893","https://openalex.org/W3170043432"],"abstract_inverted_index":{"In":[0,83,145],"the":[1,65,69,78,132,135,155],"BigData":[2],"era,":[3],"large":[4,19,143],"graph":[5,46],"datasets":[6],"are":[7,71],"becoming":[8],"increasingly":[9],"popular":[10],"due":[11],"to":[12,15,115,120,140,169],"their":[13],"capability":[14],"integrate":[16],"and":[17,91,109,161],"interconnect":[18],"sources":[20],"of":[21,68,80,134,154,159],"data":[22],"in":[23,77,131,150,157],"many":[24],"fields,":[25],"e.g.,":[26],"social":[27],"media,":[28],"biology,":[29],"communication":[30],"networks,":[31],"etc.":[32],"Graph":[33,58],"representation":[34,59,94,105],"learning":[35,56,60,95],"is":[36,138],"a":[37,45,88,102,121],"flexible":[38],"tool":[39],"that":[40],"automatically":[41],"extracts":[42],"features":[43,49,63],"from":[44],"node.":[47],"These":[48],"can":[50],"be":[51],"directly":[52],"used":[53],"for":[54,106],"machine":[55],"tasks.":[57],"approaches":[61],"producing":[62],"preserving":[64],"structural":[66,93,117],"information":[67],"graphs":[70],"still":[72],"an":[73],"open":[74],"problem,":[75],"especially":[76],"context":[79],"largescale":[81],"graphs.":[82,144],"this":[84],"paper,":[85],"we":[86,110],"propose":[87],"new":[89],"fast":[90],"scalable":[92],"approach":[96,100],"called":[97],"SparseStruct.":[98],"Our":[99],"uses":[101],"sparse":[103],"internal":[104],"each":[107,125],"node,":[108],"formally":[111],"proved":[112],"its":[113],"ability":[114],"preserve":[116],"information.":[118],"Thanks":[119],"light-weight":[122],"algorithm":[123],"where":[124],"iteration":[126],"costs":[127],"only":[128],"linear":[129],"time":[130],"number":[133],"edges,":[136],"SparseStruct":[137],"able":[139],"easily":[141],"process":[142],"addition,":[146],"it":[147],"provides":[148],"improvements":[149],"comparison":[151],"with":[152],"state":[153],"art":[156],"terms":[158],"prediction":[160],"classification":[162],"accuracy":[163],"by":[164],"also":[165],"providing":[166],"strong":[167],"robustness":[168],"noise":[170],"data.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
