{"id":"https://openalex.org/W2939242433","doi":"https://doi.org/10.1109/icassp.2019.8683424","title":"Common Randomized Shortest Paths (C-RSP): A Simple Yet Effective Framework for Multi-view Graph Embedding","display_name":"Common Randomized Shortest Paths (C-RSP): A Simple Yet Effective Framework for Multi-view Graph Embedding","publication_year":2019,"publication_date":"2019-04-17","ids":{"openalex":"https://openalex.org/W2939242433","doi":"https://doi.org/10.1109/icassp.2019.8683424","mag":"2939242433"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8683424","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683424","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5019805941","display_name":"Anuththari Gamage","orcid":"https://orcid.org/0009-0008-7774-5437"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Anuththari Gamage","raw_affiliation_strings":["Department of ECE, University of Illinois Urbana-Champaign, Urbana, IL"],"affiliations":[{"raw_affiliation_string":"Department of ECE, University of Illinois Urbana-Champaign, Urbana, IL","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060155594","display_name":"Brian Rappaport","orcid":null},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian Rappaport","raw_affiliation_strings":["School of ECE, Cornell University, Ithaca, NY"],"affiliations":[{"raw_affiliation_string":"School of ECE, Cornell University, Ithaca, NY","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004738943","display_name":"Shuchin Aeron","orcid":"https://orcid.org/0000-0002-1049-9795"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuchin Aeron","raw_affiliation_strings":["Department of ECE"],"affiliations":[{"raw_affiliation_string":"Department of ECE","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029270343","display_name":"Xiaozhe Hu","orcid":"https://orcid.org/0000-0001-7533-0416"},"institutions":[{"id":"https://openalex.org/I121934306","display_name":"Tufts University","ror":"https://ror.org/05wvpxv85","country_code":"US","type":"education","lineage":["https://openalex.org/I121934306"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaozhe Hu","raw_affiliation_strings":["Department of Mathematics, Tufts University, Medford, MA"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Tufts University, Medford, MA","institution_ids":["https://openalex.org/I121934306"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5019805941"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":0.7001,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77238277,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3542","last_page":"3546"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9966999888420105,"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":0.9966999888420105,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9955000281333923,"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":0.9952999949455261,"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/graph-embedding","display_name":"Graph embedding","score":0.64552241563797},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6010349988937378},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6000652313232422},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5165499448776245},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4912340044975281},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48625433444976807},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3401557207107544},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32411065697669983},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32077187299728394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26195937395095825}],"concepts":[{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.64552241563797},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6010349988937378},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6000652313232422},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5165499448776245},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4912340044975281},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48625433444976807},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3401557207107544},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32411065697669983},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32077187299728394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26195937395095825}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2019.8683424","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683424","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1514107797","https://openalex.org/W1576848465","https://openalex.org/W1644641054","https://openalex.org/W1655843738","https://openalex.org/W1911138687","https://openalex.org/W1985099829","https://openalex.org/W2006227471","https://openalex.org/W2019854450","https://openalex.org/W2030435519","https://openalex.org/W2050680319","https://openalex.org/W2059861509","https://openalex.org/W2065229575","https://openalex.org/W2101324110","https://openalex.org/W2102907934","https://openalex.org/W2113573459","https://openalex.org/W2132914434","https://openalex.org/W2143724577","https://openalex.org/W2154415691","https://openalex.org/W2158629280","https://openalex.org/W2219655028","https://openalex.org/W2376771266","https://openalex.org/W2405459681","https://openalex.org/W2567080747","https://openalex.org/W2792598873","https://openalex.org/W3100558473","https://openalex.org/W6639774785","https://openalex.org/W6675134712","https://openalex.org/W6682991666","https://openalex.org/W6731476941"],"related_works":["https://openalex.org/W3036264823","https://openalex.org/W3206528106","https://openalex.org/W2912814903","https://openalex.org/W2123605750","https://openalex.org/W2088740331","https://openalex.org/W3038102983","https://openalex.org/W2950907416","https://openalex.org/W1559483280","https://openalex.org/W2082479932","https://openalex.org/W2932872266"],"abstract_inverted_index":{"Real-world":[0],"data":[1,24,137],"sets":[2,25,37],"often":[3],"provide":[4],"several":[5],"types":[6],"of":[7,13,34,42,50,81,103,113,126],"information":[8],"about":[9],"the":[10,39,48,54,100,114,121,127],"same":[11,40],"set":[12,41],"entities,":[14],"showing":[15],"us":[16],"how":[17],"they":[18],"interact":[19],"from":[20,53],"different":[21],"viewpoints.":[22],"These":[23],"are":[26],"well":[27],"represented":[28],"by":[29,98],"multi-view":[30,66,83],"graphs,":[31],"which":[32,57],"consist":[33],"multiple":[35,45],"edge":[36],"across":[38,110],"nodes.":[43],"Combining":[44],"views":[46,112],"improves":[47],"quality":[49],"inferences":[51],"drawn":[52],"underlying":[55],"data,":[56],"has":[58],"led":[59],"to":[60],"increased":[61],"interest":[62],"in":[63,116],"developing":[64],"efficient":[65],"graph":[67,84],"embedding":[68,80,146],"methods.":[69],"We":[70,129],"propose":[71],"an":[72],"algorithm,":[73],"C-RSP,":[74],"that":[75,140],"generates":[76,92],"a":[77,82,93],"common":[78],"(C)":[79],"using":[85],"Randomized":[86],"Shortest":[87],"Paths":[88],"(RSP).":[89],"This":[90],"algorithm":[91],"dissimilarity":[94],"measure":[95],"between":[96,106],"nodes":[97,109],"minimizing":[99],"expected":[101],"cost":[102],"random":[104],"walks":[105],"any":[107],"two":[108],"all":[111],"graph,":[115],"doing":[117],"so":[118],"encoding":[119],"both":[120,133],"local":[122],"and":[123,135,138,147],"global":[124],"structure":[125],"graph.":[128],"test":[130],"C-RSP":[131],"on":[132],"real":[134],"synthetic":[136],"show":[139],"it":[141],"outperforms":[142],"benchmark":[143],"algorithms":[144],"at":[145],"clustering":[148],"tasks.":[149]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
