{"id":"https://openalex.org/W2060980277","doi":"https://doi.org/10.1145/1117454.1117461","title":"Relevance search and anomaly detection in bipartite graphs","display_name":"Relevance search and anomaly detection in bipartite graphs","publication_year":2005,"publication_date":"2005-12-01","ids":{"openalex":"https://openalex.org/W2060980277","doi":"https://doi.org/10.1145/1117454.1117461","mag":"2060980277"},"language":"en","primary_location":{"id":"doi:10.1145/1117454.1117461","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1117454.1117461","pdf_url":null,"source":{"id":"https://openalex.org/S4210176598","display_name":"ACM SIGKDD Explorations Newsletter","issn_l":"1931-0145","issn":["1931-0145","1931-0153"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGKDD Explorations Newsletter","raw_type":"journal-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/A5084279065","display_name":"Jimeng Sun","orcid":"https://orcid.org/0000-0003-1512-6426"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jimeng Sun","raw_affiliation_strings":["Carnegie Mellon Univ","Carnegie Mellon University"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon Univ","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112308535","display_name":"Huiming Qu","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huiming Qu","raw_affiliation_strings":["Univ. of Pittsburgh","University of Pittsburgh"],"affiliations":[{"raw_affiliation_string":"Univ. of Pittsburgh","institution_ids":["https://openalex.org/I170201317"]},{"raw_affiliation_string":"University of Pittsburgh","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078048346","display_name":"Deepayan Chakrabarti","orcid":"https://orcid.org/0000-0002-3863-4928"},"institutions":[{"id":"https://openalex.org/I2800095910","display_name":"Yahoo (Spain)","ror":"https://ror.org/03gq8sg42","country_code":"ES","type":"company","lineage":["https://openalex.org/I2800095910","https://openalex.org/I4210134091"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Deepayan Chakrabarti","raw_affiliation_strings":["Yahoo! Research","Yahoo! research,"],"affiliations":[{"raw_affiliation_string":"Yahoo! Research","institution_ids":[]},{"raw_affiliation_string":"Yahoo! research,","institution_ids":["https://openalex.org/I2800095910"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035605036","display_name":"Christos Faloutsos","orcid":"https://orcid.org/0000-0003-2996-9790"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christos Faloutsos","raw_affiliation_strings":["Univ. of Pittsburgh","University of Pittsburgh"],"affiliations":[{"raw_affiliation_string":"Univ. of Pittsburgh","institution_ids":["https://openalex.org/I170201317"]},{"raw_affiliation_string":"University of Pittsburgh","institution_ids":["https://openalex.org/I170201317"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5084279065"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":3.4832,"has_fulltext":false,"cited_by_count":69,"citation_normalized_percentile":{"value":0.92843187,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"7","issue":"2","first_page":"48","last_page":"55"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9987000226974487,"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":0.9987000226974487,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.998199999332428,"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/T11106","display_name":"Data Management and Algorithms","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.8348079919815063},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.8186107873916626},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.801620602607727},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6788149476051331},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5190356969833374},{"id":"https://openalex.org/keywords/random-walk","display_name":"Random walk","score":0.4901507794857025},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4748383164405823},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.45810532569885254},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4327124357223511},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4308792054653168},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1217677891254425}],"concepts":[{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.8348079919815063},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.8186107873916626},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.801620602607727},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6788149476051331},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5190356969833374},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.4901507794857025},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4748383164405823},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.45810532569885254},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4327124357223511},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4308792054653168},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1217677891254425},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/1117454.1117461","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1117454.1117461","pdf_url":null,"source":{"id":"https://openalex.org/S4210176598","display_name":"ACM SIGKDD Explorations Newsletter","issn_l":"1931-0145","issn":["1931-0145","1931-0153"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGKDD Explorations Newsletter","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.125.4449","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.125.4449","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.pitt.edu/~huiming/research/kddexploration05.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.331.1284","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.331.1284","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.cmu.edu/~jimeng/papers/kddexploration05.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.98.6160","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.98.6160","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://kdd.org/explorations/issues/7-2-2005-12/6-Sun.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":20,"referenced_works":["https://openalex.org/W1485732691","https://openalex.org/W1520752616","https://openalex.org/W1538524459","https://openalex.org/W1660390307","https://openalex.org/W1971421925","https://openalex.org/W1984374364","https://openalex.org/W2004951603","https://openalex.org/W2032280284","https://openalex.org/W2061122559","https://openalex.org/W2063049279","https://openalex.org/W2066636486","https://openalex.org/W2075490455","https://openalex.org/W2110325612","https://openalex.org/W2117831564","https://openalex.org/W2124591829","https://openalex.org/W2130891992","https://openalex.org/W2141806397","https://openalex.org/W2170344111","https://openalex.org/W2434205482","https://openalex.org/W4254420769"],"related_works":["https://openalex.org/W2371352078","https://openalex.org/W2953461625","https://openalex.org/W2077383796","https://openalex.org/W2372768926","https://openalex.org/W2999799752","https://openalex.org/W2080136900","https://openalex.org/W2054458431","https://openalex.org/W3013576436","https://openalex.org/W2115167491","https://openalex.org/W2567825307"],"abstract_inverted_index":{"Many":[0],"real":[1,130],"applications":[2],"can":[3],"be":[4],"modeled":[5],"using":[6,71,86],"bipartite":[7,42],"graphs,":[8],"such":[9],"as":[10],"users":[11],"vs.":[12,19,27],"files":[13],"in":[14,21,29],"a":[15,22,30],"P2P":[16],"system,":[17,25],"traders":[18],"stocks":[20],"financial":[23],"trading":[24],"conferences":[26],"authors":[28],"scientific":[31],"publication":[32],"network,":[33],"and":[34,50,76,102,119],"so":[35],"on.":[36],"We":[37,89],"introduce":[38],"two":[39],"operations":[40],"on":[41,97,128],"graphs:":[43],"1)":[44],"identifying":[45],"similar":[46],"nodes":[47,53,56],"(relevance":[48],"search),":[49],"2)":[51],"finding":[52],"connecting":[54],"irrelevant":[55],"(anomaly":[57],"detection).":[58],"And":[59],"we":[60,79,103],"propose":[61,81],"algorithms":[62,82],"to":[63,83],"compute":[64],"the":[65,91,100,106,109,122],"relevance":[66,87,94],"score":[67],"for":[68],"each":[69],"node":[70],"random":[72],"walk":[73],"with":[74,113],"restarts":[75],"graph":[77],"partitioning;":[78],"also":[80,104],"identify":[84],"anomalies,":[85],"scores.":[88],"evaluate":[90],"quality":[92],"of":[93,99,108,121],"search":[95],"based":[96],"semantics":[98],"datasets,":[101],"measure":[105],"performance":[107],"anomaly":[110],"detection":[111],"algorithm":[112],"manually":[114],"injected":[115],"anomalies.":[116],"Both":[117],"effectiveness":[118],"efficiency":[120],"methods":[123],"are":[124],"confirmed":[125],"by":[126],"experiments":[127],"several":[129],"datasets.":[131]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":6}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
