{"id":"https://openalex.org/W2789134258","doi":"https://doi.org/10.1145/3178876.3186128","title":"Low Rank Spectral Network Alignment","display_name":"Low Rank Spectral Network Alignment","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2789134258","doi":"https://doi.org/10.1145/3178876.3186128","mag":"2789134258"},"language":"en","primary_location":{"id":"doi:10.1145/3178876.3186128","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3178876.3186128","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3178876.3186128","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065393424","display_name":"Huda Nassar","orcid":"https://orcid.org/0000-0003-2909-5202"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Huda Nassar","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046315164","display_name":"Nate Veldt","orcid":"https://orcid.org/0000-0002-0117-3304"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nate Veldt","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000254294","display_name":"Shahin Mohammadi","orcid":"https://orcid.org/0000-0001-8734-2326"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shahin Mohammadi","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019202832","display_name":"Ananth Grama","orcid":"https://orcid.org/0000-0002-9378-9244"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ananth Grama","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084102378","display_name":"David F. Gleich","orcid":"https://orcid.org/0000-0002-8107-6474"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David F. Gleich","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5065393424"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":4.5577,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.95611735,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"619","last_page":"628"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9962000250816345,"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":0.9962000250816345,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9797999858856201,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.979200005531311,"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/bipartite-graph","display_name":"Bipartite graph","score":0.8361681699752808},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6512482762336731},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6398272514343262},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5906422138214111},{"id":"https://openalex.org/keywords/blossom-algorithm","display_name":"Blossom algorithm","score":0.5195584297180176},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.48469045758247375},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.4616907835006714},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4591199457645416},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4565034806728363},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.32787907123565674},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23078447580337524},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.13114407658576965}],"concepts":[{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.8361681699752808},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6512482762336731},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6398272514343262},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5906422138214111},{"id":"https://openalex.org/C61455927","wikidata":"https://www.wikidata.org/wiki/Q1030529","display_name":"Blossom algorithm","level":3,"score":0.5195584297180176},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.48469045758247375},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.4616907835006714},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4591199457645416},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4565034806728363},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.32787907123565674},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23078447580337524},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.13114407658576965},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3178876.3186128","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3178876.3186128","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3178876.3186128","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3178876.3186128","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1507964143","https://openalex.org/W1966667379","https://openalex.org/W1974682889","https://openalex.org/W2014374374","https://openalex.org/W2017822917","https://openalex.org/W2035036132","https://openalex.org/W2039872058","https://openalex.org/W2056124433","https://openalex.org/W2092986233","https://openalex.org/W2102086994","https://openalex.org/W2107427454","https://openalex.org/W2127025496","https://openalex.org/W2130237248","https://openalex.org/W2137648512","https://openalex.org/W2141185847","https://openalex.org/W2149037310","https://openalex.org/W2153929049","https://openalex.org/W2167222948","https://openalex.org/W2167538692","https://openalex.org/W2231462346","https://openalex.org/W2254156100","https://openalex.org/W2480611454","https://openalex.org/W2503629711","https://openalex.org/W2536223907","https://openalex.org/W2950700867","https://openalex.org/W2964024205","https://openalex.org/W4229990915","https://openalex.org/W4230267798"],"related_works":["https://openalex.org/W2352066879","https://openalex.org/W2561454982","https://openalex.org/W2362975861","https://openalex.org/W2348257368","https://openalex.org/W2017370158","https://openalex.org/W2367674792","https://openalex.org/W1592682627","https://openalex.org/W4295762832","https://openalex.org/W2184969544","https://openalex.org/W1964772317"],"abstract_inverted_index":{"Network":[0],"alignment":[1,188],"or":[2],"graph":[3],"matching":[4,11,134,143,167],"is":[5,41,93,107],"the":[6,39,58,68,71,96,99,112,142,145,219],"classic":[7],"problem":[8,135,168],"of":[9,28,38,61,70,98,175,228],"finding":[10],"vertices":[12],"between":[13,144],"two":[14,43,177],"graphs":[15],"with":[16,202,208,244],"applications":[17],"in":[18,67,95,111,233],"network":[19,187],"de-anonymization":[20],"and":[21,81,193,235,251],"bioinformatics.":[22],"There":[23],"exist":[24],"a":[25,33,86,130,152,158,163,170,226],"wide":[26],"variety":[27,227],"algorithms":[29,40,63,230,246],"for":[30,36,118,157],"it,":[31],"but":[32],"challenging":[34],"scenario":[35],"all":[37],"aligning":[42],"networks":[44],"without":[45],"any":[46],"information":[47],"about":[48],"which":[49,89],"nodes":[50],"might":[51],"be":[52,242],"good":[53],"matches.":[54,120],"In":[55],"this":[56,105,148],"case,":[57],"vast":[59],"majority":[60],"principled":[62],"demand":[64],"quadratic":[65],"memory":[66,91],"size":[69,97],"graphs.":[72,100,146],"We":[73,212,223],"show":[74,151],"that":[75,92,137,199],"one":[76],"such":[77],"method---the":[78],"recently":[79],"proposed":[80],"theoretically":[82],"grounded":[83],"EigenAlign":[84,117,221],"algorithm---admits":[85],"novel":[87],"implementation":[88],"requires":[90],"linear":[94],"The":[101,173],"key":[102],"step":[103],"to":[104,140,161,183,194,247],"insight":[106],"identifying":[108],"low-rank":[109,125,138,171,216],"structure":[110],"node-similarity":[113],"matrix":[114,139],"used":[115],"by":[116],"determining":[119],"With":[121],"an":[122],"exact,":[123],"closed-form":[124],"structure,":[126],"we":[127,150],"then":[128,180],"solve":[129],"maximum":[131,164],"weight":[132,165],"bipartite":[133,166],"on":[136,169,231],"produce":[141],"For":[147],"task,":[149],"new,":[153],"a-posteriori,":[154],"approximation":[155],"bound":[156],"simple":[159],"algorithm":[160,217],"approximate":[162],"matrix.":[172],"combination":[174],"our":[176,209,215],"new":[178,210],"methods":[179,204],"enables":[181],"us":[182],"tackle":[184],"much":[185],"larger":[186],"problems":[189,232],"than":[190],"previously":[191],"possible":[192],"do":[195],"so":[196],"quickly.":[197],"Problems":[198],"take":[200,205],"hours":[201],"existing":[203,229,245],"only":[206],"seconds":[207],"algorithm.":[211],"thoroughly":[213],"validate":[214],"against":[218],"original":[220],"approach.":[222],"also":[224,241],"compare":[225],"bioinformatics":[234],"social":[236],"networks.":[237],"Our":[238],"approach":[239],"can":[240],"combined":[243],"improve":[248],"their":[249],"performance":[250],"speed.":[252]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-17T09:09:15.849793","created_date":"2025-10-10T00:00:00"}