{"id":"https://openalex.org/W4381744422","doi":"https://doi.org/10.1109/cscwd57460.2023.10152845","title":"Network Embedding with Enhanced Feature Representations for Link Prediction","display_name":"Network Embedding with Enhanced Feature Representations for Link Prediction","publication_year":2023,"publication_date":"2023-05-24","ids":{"openalex":"https://openalex.org/W4381744422","doi":"https://doi.org/10.1109/cscwd57460.2023.10152845"},"language":"en","primary_location":{"id":"doi:10.1109/cscwd57460.2023.10152845","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd57460.2023.10152845","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 26th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","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/A5058194445","display_name":"Weisheng Li","orcid":"https://orcid.org/0000-0002-9033-8245"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weisheng Li","raw_affiliation_strings":["South China Normal University,School of Computer Science,Guangzhou,China","Pazhou Lab, Guangzhou, China","School of Computer Science, South China Normal University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China Normal University,School of Computer Science,Guangzhou,China","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"Pazhou Lab, Guangzhou, China","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100686411","display_name":"Wentao Chen","orcid":"https://orcid.org/0000-0002-4994-8682"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wentao Chen","raw_affiliation_strings":["South China Normal University,School of Physics and Telecommunication Engineering,Guangzhou,China","School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China Normal University,School of Physics and Telecommunication Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052605989","display_name":"Zhihong Pan","orcid":"https://orcid.org/0000-0002-2540-8083"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihong Pan","raw_affiliation_strings":["South China Normal University,School of Artificial Intelligence,Foshan,China","School of Artificial Intelligence, South China Normal University, Foshan, China"],"affiliations":[{"raw_affiliation_string":"South China Normal University,School of Artificial Intelligence,Foshan,China","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"School of Artificial Intelligence, South China Normal University, Foshan, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054687122","display_name":"Yuanfei Deng","orcid":"https://orcid.org/0000-0003-3912-6383"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanfei Deng","raw_affiliation_strings":["South China Normal University,School of Computer Science,Guangzhou,China","School of Computer Science, South China Normal University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China Normal University,School of Computer Science,Guangzhou,China","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"School of Computer Science, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082185821","display_name":"Yong Tang","orcid":"https://orcid.org/0000-0002-8199-3985"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Tang","raw_affiliation_strings":["South China Normal University,School of Computer Science,Guangzhou,China","Pazhou Lab, Guangzhou, China","School of Computer Science, South China Normal University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China Normal University,School of Computer Science,Guangzhou,China","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"Pazhou Lab, Guangzhou, China","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026139698","display_name":"Chaobo He","orcid":"https://orcid.org/0000-0002-6651-1175"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaobo He","raw_affiliation_strings":["South China Normal University,School of Computer Science,Guangzhou,China","School of Computer Science, South China Normal University, Guangzhou, China","Pazhou Lab, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China Normal University,School of Computer Science,Guangzhou,China","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"School of Computer Science, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"Pazhou Lab, Guangzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5058194445"],"corresponding_institution_ids":["https://openalex.org/I187400657"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07203474,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1324","last_page":"1329"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994999766349792,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9991000294685364,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9765999913215637,"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":0.7429075837135315},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6894152760505676},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6175526976585388},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5766164660453796},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5523208975791931},{"id":"https://openalex.org/keywords/link","display_name":"Link (geometry)","score":0.5369930267333984},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4826236665248871},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.4485968351364136},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4416292607784271},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4269822835922241},{"id":"https://openalex.org/keywords/random-walk","display_name":"Random walk","score":0.4268597960472107},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41724923253059387},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3766253590583801},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3544795513153076},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1841450035572052}],"concepts":[{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.7429075837135315},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6894152760505676},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6175526976585388},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5766164660453796},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5523208975791931},{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.5369930267333984},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4826236665248871},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.4485968351364136},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4416292607784271},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4269822835922241},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.4268597960472107},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41724923253059387},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3766253590583801},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3544795513153076},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1841450035572052},{"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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cscwd57460.2023.10152845","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd57460.2023.10152845","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 26th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":0,"referenced_works":[],"related_works":["https://openalex.org/W4377019474","https://openalex.org/W2602709848","https://openalex.org/W4281939267","https://openalex.org/W2470758182","https://openalex.org/W2038143369","https://openalex.org/W4308166597","https://openalex.org/W2998460306","https://openalex.org/W2079771573","https://openalex.org/W4240697234","https://openalex.org/W2997890342"],"abstract_inverted_index":{"Link":[0],"prediction":[1,42,103],"is":[2,193,204],"a":[3,18,25,90,136],"hot":[4],"research":[5],"topic":[6],"in":[7,24,39],"graph":[8],"data":[9],"analytics,":[10],"which":[11],"aims":[12],"to":[13,30,76,140],"identify":[14],"the":[15,28,63,116,147,156,176,184,187,201],"likelihood":[16],"of":[17,62,149,186,189,200],"future":[19],"connection":[20],"between":[21,131,191],"two":[22,214],"nodes":[23,192],"network.":[26],"Among":[27],"approaches":[29],"link":[31,41,102],"prediction,":[32],"network":[33,48,67,79,95,165],"embedding":[34,49,68,96],"has":[35],"gained":[36],"tremendous":[37],"popularity":[38],"tackling":[40],"tasks.":[43],"Basically,":[44],"there":[45],"are":[46,113,122,173],"several":[47,211],"methods,":[50],"such":[51],"as":[52],"matrix":[53],"factorization,":[54],"random":[55,138],"walk,":[56],"and":[57,81,110,128],"deep":[58,196],"learning.":[59],"However,":[60],"most":[61],"existing":[64],"methods":[65],"for":[66,101,179],"solely":[69],"rely":[70],"on":[71,213],"structure":[72,80,106],"information":[73],"or":[74],"fail":[75],"effectively":[77,161],"combine":[78],"feature":[82,99,151],"data.":[83],"To":[84],"this":[85,87],"end,":[86],"paper":[88],"proposes":[89],"novel":[91],"method":[92,203],"that":[93],"learns":[94],"with":[97,210],"enhanced":[98],"representations":[100],"(EFRLP).":[104],"Specifically,":[105],"graphs,":[107,109],"bipartite":[108,120,126],"co-feature":[111],"graphs":[112,121,127],"generated":[114],"from":[115],"attributed":[117],"network,":[118],"weighted":[119],"then":[123],"built":[124],"over":[125],"correlation":[129],"weights":[130],"features.":[132],"We":[133],"further":[134],"adopt":[135],"biased":[137],"walk":[139],"obtain":[141],"more":[142],"representative":[143],"node":[144,171],"sequences.":[145],"With":[146],"help":[148],"enriched":[150],"representations,":[152],"not":[153],"only":[154],"can":[155,167],"higher-order":[157],"semantic":[158],"relationships":[159],"be":[160,168],"captured":[162],"but":[163],"also":[164],"sparsity":[166],"alleviated.":[169],"Then,":[170],"sequences":[172],"selected":[174],"into":[175],"Skip-Gram":[177],"model":[178],"learning":[180],"low-dimensional":[181],"embeddings.":[182],"Finally,":[183],"probability":[185],"existence":[188],"edges":[190],"predicted":[194],"by":[195,206],"fusion.":[197],"The":[198],"effectiveness":[199],"EFRLP":[202],"demonstrated":[205],"extensive":[207],"comparison":[208],"experiments":[209],"baselines":[212],"real-world":[215],"datasets.":[216]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}