{"id":"https://openalex.org/W2003707464","doi":"https://doi.org/10.1145/1835804.1835837","title":"New perspectives and methods in link prediction","display_name":"New perspectives and methods in link prediction","publication_year":2010,"publication_date":"2010-07-25","ids":{"openalex":"https://openalex.org/W2003707464","doi":"https://doi.org/10.1145/1835804.1835837","mag":"2003707464"},"language":"en","primary_location":{"id":"doi:10.1145/1835804.1835837","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1835804.1835837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5079266855","display_name":"Ryan N. Lichtenwalter","orcid":null},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ryan N. Lichtenwalter","raw_affiliation_strings":["The University of Notre Dame, South Bend, IN, USA"],"affiliations":[{"raw_affiliation_string":"The University of Notre Dame, South Bend, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087546047","display_name":"Jake T. Lussier","orcid":null},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jake T. Lussier","raw_affiliation_strings":["The University of Notre Dame, South Bend, IN, USA"],"affiliations":[{"raw_affiliation_string":"The University of Notre Dame, South Bend, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068157871","display_name":"Nitesh V. Chawla","orcid":"https://orcid.org/0000-0003-3932-5956"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nitesh V. Chawla","raw_affiliation_strings":["The University of Notre Dame, South Bend, IN, USA"],"affiliations":[{"raw_affiliation_string":"The University of Notre Dame, South Bend, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5079266855"],"corresponding_institution_ids":["https://openalex.org/I107639228"],"apc_list":null,"apc_paid":null,"fwci":26.3296,"has_fulltext":false,"cited_by_count":672,"citation_normalized_percentile":{"value":0.99779889,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"243","last_page":"252"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9976000189781189,"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":0.9761000275611877,"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/generality","display_name":"Generality","score":0.8520736694335938},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7529761791229248},{"id":"https://openalex.org/keywords/link","display_name":"Link (geometry)","score":0.6898386478424072},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6597280502319336},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6007607579231262},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.594353973865509},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5531880259513855},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4758557975292206},{"id":"https://openalex.org/keywords/observational-study","display_name":"Observational study","score":0.41732341051101685},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4133610725402832},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3855883777141571},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.23050644993782043},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13366687297821045},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1031615138053894}],"concepts":[{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.8520736694335938},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7529761791229248},{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.6898386478424072},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6597280502319336},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6007607579231262},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.594353973865509},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5531880259513855},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4758557975292206},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.41732341051101685},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4133610725402832},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3855883777141571},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.23050644993782043},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13366687297821045},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1031615138053894},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1835804.1835837","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1835804.1835837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.363.3951","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.363.3951","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cse.nd.edu/~nchawla/papers/KDD10.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1504694836","https://openalex.org/W1556758605","https://openalex.org/W1570448133","https://openalex.org/W1831729862","https://openalex.org/W1903894141","https://openalex.org/W2026417691","https://openalex.org/W2037933327","https://openalex.org/W2048596679","https://openalex.org/W2096942889","https://openalex.org/W2125055259","https://openalex.org/W2125082260","https://openalex.org/W2140584250","https://openalex.org/W2145845082","https://openalex.org/W2148143831","https://openalex.org/W2154454189","https://openalex.org/W2155048531","https://openalex.org/W2768375068","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W2966207845","https://openalex.org/W3100447784","https://openalex.org/W4232932184","https://openalex.org/W6638557778","https://openalex.org/W6639897565"],"related_works":["https://openalex.org/W3148060700","https://openalex.org/W3080681248","https://openalex.org/W4376646226","https://openalex.org/W3047177827","https://openalex.org/W4287685660","https://openalex.org/W2057778272","https://openalex.org/W4319302697","https://openalex.org/W2986085304","https://openalex.org/W2163389298","https://openalex.org/W205223620"],"abstract_inverted_index":{"This":[0],"paper":[1],"examines":[2],"important":[3],"factors":[4,66,81],"for":[5,16,141],"link":[6,133,162],"prediction":[7,18,21,163],"in":[8,22,68,130],"networks":[9,24],"and":[10,70,110,114,135],"provides":[11],"a":[12,26,88,92,155],"general,":[13],"high-performance":[14],"framework":[15,90,158],"the":[17,31,58,85,142,149],"task.":[19],"Link":[20],"sparse":[23,131],"presents":[25],"significant":[27,67],"challenge":[28],"due":[29],"to":[30,39,61,154],"inherent":[32],"disproportion":[33],"of":[34,87,95,103,112,148],"links":[35,40],"that":[36,41,159],"can":[37],"form":[38],"do":[42],"form.":[43],"Previous":[44],"research":[45],"has":[46],"typically":[47],"approached":[48],"this":[49,55,76],"as":[50,98],"an":[51,120,137],"unsupervised":[52,161],"problem.":[53],"While":[54],"is":[56],"not":[57],"first":[59,83],"work":[60],"explore":[62],"supervised":[63,89],"learning,":[64],"many":[65],"influencing":[69],"guiding":[71],"classification":[72],"remain":[73],"unexplored.":[74],"In":[75],"paper,":[77],"we":[78],"consider":[79],"these":[80],"by":[82,165],"motivating":[84],"use":[86],"through":[91],"careful":[93,146],"investigation":[94],"issues":[96,151],"such":[97],"network":[99,132],"observational":[100],"period,":[101],"generality":[102],"existing":[104],"methods,":[105],"variance":[106],"reduction,":[107],"topological":[108],"causes":[109],"degrees":[111],"imbalance,":[113],"sampling":[115],"approaches.":[116],"We":[117],"also":[118],"present":[119],"effective":[121],"flow-based":[122],"predicting":[123],"algorithm,":[124],"offer":[125],"formal":[126],"bounds":[127],"on":[128],"imbalance":[129],"prediction,":[134],"employ":[136],"evaluation":[138],"method":[139],"appropriate":[140],"observed":[143],"imbalance.":[144],"Our":[145],"consideration":[147],"above":[150],"ultimately":[152],"leads":[153],"completely":[156],"general":[157],"outperforms":[160],"methods":[164],"more":[166],"than":[167],"30%":[168],"AUC.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":22},{"year":2021,"cited_by_count":50},{"year":2020,"cited_by_count":46},{"year":2019,"cited_by_count":48},{"year":2018,"cited_by_count":50},{"year":2017,"cited_by_count":60},{"year":2016,"cited_by_count":82},{"year":2015,"cited_by_count":67},{"year":2014,"cited_by_count":82},{"year":2013,"cited_by_count":43},{"year":2012,"cited_by_count":46}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}