{"id":"https://openalex.org/W2073595285","doi":"https://doi.org/10.1145/2487575.2487692","title":"Mining discriminative subgraphs from global-state networks","display_name":"Mining discriminative subgraphs from global-state networks","publication_year":2013,"publication_date":"2013-08-11","ids":{"openalex":"https://openalex.org/W2073595285","doi":"https://doi.org/10.1145/2487575.2487692","mag":"2073595285"},"language":"en","primary_location":{"id":"doi:10.1145/2487575.2487692","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2487575.2487692","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5054697900","display_name":"Sayan Ranu","orcid":"https://orcid.org/0000-0003-4147-9372"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sayan Ranu","raw_affiliation_strings":["IBM Research, Bangalore, India","IBM Research. Bangalore, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research, Bangalore, India","institution_ids":["https://openalex.org/I4210103279"]},{"raw_affiliation_string":"IBM Research. Bangalore, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017076828","display_name":"Minh Hoang","orcid":null},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Minh Hoang","raw_affiliation_strings":["University of California, Santa Barbara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036639779","display_name":"Ambuj K. Singh","orcid":"https://orcid.org/0000-0002-1997-7140"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ambuj Singh","raw_affiliation_strings":["University of California, Santa Barbara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"509","last_page":"517"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9975000023841858,"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":0.9918000102043152,"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/discriminative-model","display_name":"Discriminative model","score":0.8533268570899963},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.724252462387085},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.5340067148208618},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5201659202575684},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5142066478729248},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.511277437210083},{"id":"https://openalex.org/keywords/complex-network","display_name":"Complex network","score":0.47245410084724426},{"id":"https://openalex.org/keywords/global-network","display_name":"Global network","score":0.47148677706718445},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40848416090011597},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38393837213516235},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16612878441810608}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8533268570899963},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.724252462387085},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.5340067148208618},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5201659202575684},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5142066478729248},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.511277437210083},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.47245410084724426},{"id":"https://openalex.org/C123138037","wikidata":"https://www.wikidata.org/wiki/Q5570871","display_name":"Global network","level":2,"score":0.47148677706718445},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40848416090011597},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38393837213516235},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16612878441810608},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2487575.2487692","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2487575.2487692","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1503334950","https://openalex.org/W1515242458","https://openalex.org/W1967380540","https://openalex.org/W1970074386","https://openalex.org/W1983219224","https://openalex.org/W2070962918","https://openalex.org/W2102039273","https://openalex.org/W2114062029","https://openalex.org/W2115119998","https://openalex.org/W2116063398","https://openalex.org/W2116650325","https://openalex.org/W2124387466","https://openalex.org/W2139104449","https://openalex.org/W2141777143","https://openalex.org/W2143211346","https://openalex.org/W2160514535","https://openalex.org/W2160655616","https://openalex.org/W2164281374","https://openalex.org/W2364425459","https://openalex.org/W4296184861","https://openalex.org/W6680366265"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W1482209366","https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2008824761","https://openalex.org/W4385196225"],"abstract_inverted_index":{"Global-state":[0],"networks":[1,49],"provide":[2],"a":[3,18,22,34,75,90,166],"powerful":[4],"mechanism":[5],"to":[6,52,94,125,139,145],"model":[7],"the":[8,39,54,62,67,71,105,112,127,133,146],"increasing":[9],"heterogeneity":[10],"in":[11,158],"data":[12],"generated":[13],"by":[14],"current":[15],"systems.":[16],"Such":[17],"network":[19,25,36,76,148],"comprises":[20],"of":[21,24,41,74,114,135,160,168,173],"series":[23],"snapshots":[26],"with":[27],"dynamic":[28],"local":[29,72],"states":[30],"at":[31,169],"nodes,":[32],"and":[33,65,77,88,118],"global":[35,63],"state":[37,64],"indicating":[38],"occurrence":[40],"an":[42,115],"event.":[43],"Mining":[44],"discriminative":[45,97],"subgraphs":[46,98],"from":[47,99],"global-state":[48,101],"allows":[50],"us":[51],"identify":[53],"influential":[55],"sub-networks":[56],"that":[57,143],"have":[58],"maximum":[59],"impact":[60],"on":[61,123,152],"unearth":[66],"complex":[68],"relationships":[69],"between":[70],"entities":[73],"their":[78],"collective":[79],"behavior.":[80],"In":[81],"this":[82,86],"paper,":[83],"we":[84,110,131],"explore":[85],"problem":[87],"design":[89],"technique":[91],"called":[92],"MINDS":[93,164],"mine":[95],"minimally":[96],"large":[100],"networks.":[102],"To":[103],"combat":[104],"exponential":[106],"subgraph":[107],"search":[108],"space,":[109],"derive":[111],"concept":[113],"edit":[116],"map":[117],"perform":[119],"Metropolis":[120],"Hastings":[121],"sampling":[122],"it":[124],"compute":[126],"answer":[128],"set.":[129],"Furthermore,":[130],"formulate":[132],"idea":[134],"network-constrained":[136],"decision":[137],"trees":[138],"learn":[140],"prediction":[141,161],"models":[142],"adhere":[144],"underlying":[147],"structure.":[149],"Extensive":[150],"experiments":[151],"real":[153],"datasets":[154],"demonstrate":[155],"excellent":[156],"accuracy":[157],"terms":[159],"quality.":[162],"Additionally,":[163],"achieves":[165],"speed-up":[167],"least":[170],"four":[171],"orders":[172],"magnitude":[174],"over":[175],"baseline":[176],"techniques.":[177]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}