{"id":"https://openalex.org/W3028551553","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206976","title":"Learning Representations using Spectral-Biased Random Walks on Graphs","display_name":"Learning Representations using Spectral-Biased Random Walks on Graphs","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3028551553","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206976","mag":"3028551553"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9206976","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206976","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2005.09752","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101841889","display_name":"Charu Sharma","orcid":"https://orcid.org/0000-0003-2518-5008"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Charu Sharma","raw_affiliation_strings":["Dept. of Computer Science & Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, India","Indian Institute of Technology Hyderabad,Dept. of Computer Science & Engineering,Kandi, Sangareddy,India"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, India","institution_ids":["https://openalex.org/I65181880"]},{"raw_affiliation_string":"Indian Institute of Technology Hyderabad,Dept. of Computer Science & Engineering,Kandi, Sangareddy,India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038562115","display_name":"Jatin Chauhan","orcid":"https://orcid.org/0000-0002-0209-3883"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jatin Chauhan","raw_affiliation_strings":["Dept. of Computer Science & Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, India","Indian Institute of Technology Hyderabad,Dept. of Computer Science & Engineering,Kandi, Sangareddy,India"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, India","institution_ids":["https://openalex.org/I65181880"]},{"raw_affiliation_string":"Indian Institute of Technology Hyderabad,Dept. of Computer Science & Engineering,Kandi, Sangareddy,India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052626178","display_name":"Manohar Kaul","orcid":null},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manohar Kaul","raw_affiliation_strings":["Dept. of Computer Science & Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, India","[Indian Institute of Technology, Hyderabad]"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, India","institution_ids":["https://openalex.org/I65181880"]},{"raw_affiliation_string":"[Indian Institute of Technology, Hyderabad]","institution_ids":["https://openalex.org/I65181880"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101841889"],"corresponding_institution_ids":["https://openalex.org/I65181880"],"apc_list":null,"apc_paid":null,"fwci":0.14685955,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.52486255,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"286","issue":null,"first_page":"1","last_page":"8"},"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":0.9993000030517578,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9854000210762024,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/random-walk","display_name":"Random walk","score":0.7502378225326538},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6304365396499634},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6005738973617554},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5443872213363647},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4876945912837982},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4860582649707794},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.45108872652053833},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35670092701911926},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33606505393981934},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2899478077888489}],"concepts":[{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.7502378225326538},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6304365396499634},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6005738973617554},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5443872213363647},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4876945912837982},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4860582649707794},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.45108872652053833},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35670092701911926},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33606505393981934},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2899478077888489},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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},{"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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9206976","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206976","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2005.09752","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2005.09752","pdf_url":"https://arxiv.org/pdf/2005.09752","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:3028551553","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2005.09752.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2005.09752","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2005.09752","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2005.09752","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2005.09752","pdf_url":"https://arxiv.org/pdf/2005.09752","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.7799999713897705,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3028551553.pdf","grobid_xml":"https://content.openalex.org/works/W3028551553.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1600293573","https://openalex.org/W1614298861","https://openalex.org/W1979104937","https://openalex.org/W2007444087","https://openalex.org/W2008620264","https://openalex.org/W2036120890","https://openalex.org/W2037933327","https://openalex.org/W2060540871","https://openalex.org/W2117831564","https://openalex.org/W2131744502","https://openalex.org/W2142498761","https://openalex.org/W2153959628","https://openalex.org/W2154454189","https://openalex.org/W2154851992","https://openalex.org/W2156718197","https://openalex.org/W2163485494","https://openalex.org/W2164021670","https://openalex.org/W2168627253","https://openalex.org/W2186385828","https://openalex.org/W2294347342","https://openalex.org/W2519887557","https://openalex.org/W2554952599","https://openalex.org/W2558460151","https://openalex.org/W2607500032","https://openalex.org/W2610278296","https://openalex.org/W2742503211","https://openalex.org/W2796284048","https://openalex.org/W2890855364","https://openalex.org/W2962756421","https://openalex.org/W2963312446","https://openalex.org/W2963325573","https://openalex.org/W2963757395","https://openalex.org/W3104097132","https://openalex.org/W4232932184","https://openalex.org/W6636510571","https://openalex.org/W6679775712","https://openalex.org/W6681029592","https://openalex.org/W6682755970","https://openalex.org/W6684354137","https://openalex.org/W6687119193","https://openalex.org/W6697195335","https://openalex.org/W6699364125","https://openalex.org/W6726873649","https://openalex.org/W6730084236","https://openalex.org/W6740572265","https://openalex.org/W6748856961","https://openalex.org/W6749965875"],"related_works":["https://openalex.org/W3091246499","https://openalex.org/W3211610195","https://openalex.org/W2786552636","https://openalex.org/W2607730119","https://openalex.org/W2990998448","https://openalex.org/W3084003337","https://openalex.org/W2964271403","https://openalex.org/W2993925163","https://openalex.org/W2982697778","https://openalex.org/W3015279468","https://openalex.org/W3202302784","https://openalex.org/W3003354019","https://openalex.org/W2136116685","https://openalex.org/W3123080870","https://openalex.org/W3151807233","https://openalex.org/W3044177866","https://openalex.org/W3185942086","https://openalex.org/W3186065747","https://openalex.org/W3094478993","https://openalex.org/W3198352794"],"abstract_inverted_index":{"Several":[0],"state-of-the-art":[1,127],"neural":[2],"graph":[3,25],"embedding":[4,129],"methods":[5,148],"are":[6,34],"based":[7,90],"on":[8,91,131,149],"short":[9],"random":[10],"walks":[11],"(stochastic":[12],"processes)":[13],"because":[14],"of":[15,18,50,94,109,135],"their":[16],"ease":[17],"computation,":[19],"simplicity":[20],"in":[21,36,43],"capturing":[22],"complex":[23],"local":[24],"properties,":[26],"scalability,":[27],"and":[28,138,153],"interpretibility.":[29],"In":[30,57],"this":[31,44,84],"work,":[32],"we":[33],"interested":[35],"studying":[37],"how":[38],"much":[39],"a":[40,63,73,87,101,110,115,132],"probabilistic":[41],"bias":[42],"stochastic":[45],"process":[46],"affects":[47],"the":[48,51,55,77,92,95,107],"quality":[49],"nodes":[52,69],"picked":[53],"by":[54],"process.":[56],"particular,":[58],"our":[59,123,141],"biased":[60],"walk,":[61],"with":[62,114],"certain":[64],"probability,":[65],"favors":[66],"movement":[67],"towards":[68],"whose":[70],"neighborhoods":[71],"bear":[72],"structural":[74],"resemblance":[75],"to":[76],"current":[78],"node's":[79,96],"neighborhood.":[80],"We":[81,105,120],"succinctly":[82],"capture":[83],"neighborhood":[85,97],"as":[86,100],"probability":[88],"measure":[89],"spectrum":[93],"subgraph":[98],"represented":[99],"normalized":[102],"laplacian":[103],"matrix.":[104],"propose":[106],"use":[108],"paragraph":[111],"vector":[112],"model":[113],"novel":[116],"Wasserstein":[117],"regularization":[118],"term.":[119],"empirically":[121],"evaluate":[122],"approach":[124],"against":[125],"several":[126],"node":[128,154],"techniques":[130],"wide":[133],"variety":[134],"real-world":[136],"datasets":[137],"demonstrate":[139],"that":[140],"proposed":[142],"method":[143],"significantly":[144],"improves":[145],"upon":[146],"existing":[147],"both":[150],"link":[151],"prediction":[152],"classification":[155],"tasks.":[156]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}