{"id":"https://openalex.org/W2097056866","doi":"https://doi.org/10.1145/1830252.1830272","title":"Frequent subgraph discovery in dynamic networks","display_name":"Frequent subgraph discovery in dynamic networks","publication_year":2010,"publication_date":"2010-07-24","ids":{"openalex":"https://openalex.org/W2097056866","doi":"https://doi.org/10.1145/1830252.1830272","mag":"2097056866"},"language":"en","primary_location":{"id":"doi:10.1145/1830252.1830272","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1830252.1830272","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighth Workshop on Mining and Learning with Graphs","raw_type":"proceedings-article"},"type":"conference-paper","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/A5037034767","display_name":"Bianca Wackersreuther","orcid":null},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bianca Wackersreuther","raw_affiliation_strings":["University of Munich, Munich, Germany","University of Munich, Munich, GERMANY#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]},{"raw_affiliation_string":"University of Munich, Munich, GERMANY#TAB#","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081342700","display_name":"Peter Wackersreuther","orcid":null},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Peter Wackersreuther","raw_affiliation_strings":["University of Munich, Munich, Germany","University of Munich, Munich, GERMANY#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]},{"raw_affiliation_string":"University of Munich, Munich, GERMANY#TAB#","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113468919","display_name":"Annahita Oswald","orcid":null},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Annahita Oswald","raw_affiliation_strings":["University of Munich, Munich, Germany","University of Munich, Munich, GERMANY#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]},{"raw_affiliation_string":"University of Munich, Munich, GERMANY#TAB#","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062860517","display_name":"Christian B\u00f6hm","orcid":"https://orcid.org/0000-0002-2237-9969"},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christian B\u00f6hm","raw_affiliation_strings":["University of Munich, Munich, Germany","University of Munich, Munich, GERMANY#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]},{"raw_affiliation_string":"University of Munich, Munich, GERMANY#TAB#","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074540538","display_name":"Karsten Borgwardt","orcid":"https://orcid.org/0000-0001-7221-2393"},"institutions":[{"id":"https://openalex.org/I4210112925","display_name":"Max Planck Institute for Biological Cybernetics","ror":"https://ror.org/026nmvv73","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210112925"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Karsten M. Borgwardt","raw_affiliation_strings":["MPIs for Developmental Biology and Biological Cybernetics, T\u00fcbingen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MPIs for Developmental Biology and Biological Cybernetics, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I4210112925"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"155","last_page":"162"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9926000237464905,"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"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9847999811172485,"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/computer-science","display_name":"Computer science","score":0.7171677947044373},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5343510508537292},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4284043312072754},{"id":"https://openalex.org/keywords/induced-subgraph-isomorphism-problem","display_name":"Induced subgraph isomorphism problem","score":0.42640697956085205},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4231155812740326},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35257354378700256},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21796172857284546},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.09865444898605347}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7171677947044373},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5343510508537292},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4284043312072754},{"id":"https://openalex.org/C191241153","wikidata":"https://www.wikidata.org/wiki/Q6027240","display_name":"Induced subgraph isomorphism problem","level":5,"score":0.42640697956085205},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4231155812740326},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35257354378700256},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21796172857284546},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.09865444898605347},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1830252.1830272","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1830252.1830272","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighth Workshop on Mining and Learning with Graphs","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.mpg.de:item_3009198","is_oa":false,"landing_page_url":"http://hdl.handle.net/21.11116/0000-0002-814E-5","pdf_url":null,"source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"MLG '10: Proceedings of the Eighth Workshop on Mining and Learning with Graphs","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W230663966","https://openalex.org/W1592376869","https://openalex.org/W1605319014","https://openalex.org/W2011039300","https://openalex.org/W2054774141","https://openalex.org/W2066235893","https://openalex.org/W2102135646","https://openalex.org/W2103017472","https://openalex.org/W2110699703","https://openalex.org/W2111708605","https://openalex.org/W2120423098","https://openalex.org/W2124533460","https://openalex.org/W2124996875","https://openalex.org/W2132582966","https://openalex.org/W2136593687","https://openalex.org/W2142460132","https://openalex.org/W2147137793","https://openalex.org/W2161917555","https://openalex.org/W2162945593","https://openalex.org/W2167188257","https://openalex.org/W2170726034"],"related_works":["https://openalex.org/W231720905","https://openalex.org/W1482551403","https://openalex.org/W2532922352","https://openalex.org/W2128390795","https://openalex.org/W2915540008","https://openalex.org/W2604893261","https://openalex.org/W3002471523","https://openalex.org/W2604114816","https://openalex.org/W2361654510","https://openalex.org/W2393701947"],"abstract_inverted_index":{"In":[0,57,73],"many":[1],"application":[2],"domains,":[3],"graphs":[4,35,79],"are":[5,76],"utilized":[6],"to":[7,18,65,99],"model":[8],"entities":[9],"and":[10,13,83],"their":[11],"relationships,":[12],"graph":[14],"mining":[15,30,90],"is":[16],"important":[17],"detect":[19],"patterns":[20],"within":[21],"these":[22],"relationships.":[23],"While":[24],"the":[25,46,117],"majority":[26],"of":[27,48,52,55,120],"recent":[28,42],"data":[29],"techniques":[31],"deal":[32],"with":[33,80],"static":[34],"that":[36],"do":[37],"not":[38],"change":[39],"over":[40,86],"time,":[41],"years":[43],"have":[44],"witnessed":[45],"advent":[47],"an":[49,106],"increasing":[50],"number":[51],"time":[53],"series":[54],"graphs.":[56,104],"this":[58],"paper,":[59],"we":[60,75],"define":[61],"a":[62,111],"novel":[63],"framework":[64,98],"perform":[66],"frequent":[67],"subgraph":[68,89],"discovery":[69],"in":[70],"dynamic":[71,78,103],"networks.":[72],"particular,":[74],"considering":[77],"edge":[81,84],"insertions":[82],"deletions":[85],"time.":[87],"Existing":[88],"algorithms":[91],"can":[92],"be":[93],"easily":[94],"integrated":[95],"into":[96],"our":[97,121],"make":[100],"them":[101],"handle":[102],"Finally,":[105],"extensive":[107],"experimental":[108],"evaluation":[109],"on":[110],"large":[112],"real-world":[113],"case":[114],"study":[115],"confirms":[116],"practical":[118],"feasibility":[119],"approach.":[122]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}