{"id":"https://openalex.org/W4281811833","doi":"https://doi.org/10.1145/3514221.3517859","title":"Hunting Temporal Bumps in Graphs with Dynamic Vertex Properties","display_name":"Hunting Temporal Bumps in Graphs with Dynamic Vertex Properties","publication_year":2022,"publication_date":"2022-06-10","ids":{"openalex":"https://openalex.org/W4281811833","doi":"https://doi.org/10.1145/3514221.3517859"},"language":"en","primary_location":{"id":"doi:10.1145/3514221.3517859","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3514221.3517859","pdf_url":null,"source":{"id":"https://openalex.org/S4363608845","display_name":"Proceedings of the 2022 International Conference on Management of Data","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 International Conference on Management of Data","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/A5101613334","display_name":"Yahui Sun","orcid":"https://orcid.org/0000-0003-3730-8538"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yahui Sun","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006980420","display_name":"Shuai Ma","orcid":"https://orcid.org/0000-0002-4050-0443"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Ma","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062357883","display_name":"Bin Cui","orcid":"https://orcid.org/0000-0003-1681-4677"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Cui","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101613334"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":0.4062,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.48293515,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"874","last_page":"888"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9987999796867371,"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":0.9962000250816345,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7544490098953247},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.6519962549209595},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6409091353416443},{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.6323347091674805},{"id":"https://openalex.org/keywords/time-complexity","display_name":"Time complexity","score":0.5453947186470032},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.5430902242660522},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.5363510847091675},{"id":"https://openalex.org/keywords/interval-graph","display_name":"Interval graph","score":0.523280918598175},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49539148807525635},{"id":"https://openalex.org/keywords/running-time","display_name":"Running time","score":0.45749765634536743},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4571930468082428},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4194521903991699},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3832796514034271},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.33987191319465637},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.32808464765548706},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27049362659454346},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.212123304605484},{"id":"https://openalex.org/keywords/pathwidth","display_name":"Pathwidth","score":0.11815464496612549},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.11398643255233765}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7544490098953247},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.6519962549209595},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6409091353416443},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.6323347091674805},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.5453947186470032},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.5430902242660522},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.5363510847091675},{"id":"https://openalex.org/C67810366","wikidata":"https://www.wikidata.org/wiki/Q835942","display_name":"Interval graph","level":5,"score":0.523280918598175},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49539148807525635},{"id":"https://openalex.org/C3017489831","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Running time","level":2,"score":0.45749765634536743},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4571930468082428},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4194521903991699},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3832796514034271},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.33987191319465637},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.32808464765548706},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27049362659454346},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.212123304605484},{"id":"https://openalex.org/C43517604","wikidata":"https://www.wikidata.org/wiki/Q7144893","display_name":"Pathwidth","level":4,"score":0.11815464496612549},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11398643255233765},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3514221.3517859","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3514221.3517859","pdf_url":null,"source":{"id":"https://openalex.org/S4363608845","display_name":"Proceedings of the 2022 International Conference on Management of Data","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 International Conference on Management of Data","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W195165020","https://openalex.org/W248604449","https://openalex.org/W1964419312","https://openalex.org/W1978291048","https://openalex.org/W1983481354","https://openalex.org/W1991055327","https://openalex.org/W1996668544","https://openalex.org/W2001139415","https://openalex.org/W2001681959","https://openalex.org/W2014577670","https://openalex.org/W2043905543","https://openalex.org/W2055518297","https://openalex.org/W2058148593","https://openalex.org/W2060523933","https://openalex.org/W2068362339","https://openalex.org/W2122990988","https://openalex.org/W2123087902","https://openalex.org/W2123442845","https://openalex.org/W2140951480","https://openalex.org/W2167598145","https://openalex.org/W2167641446","https://openalex.org/W2303924406","https://openalex.org/W2398361527","https://openalex.org/W2404243041","https://openalex.org/W2406996709","https://openalex.org/W2533098469","https://openalex.org/W2562676961","https://openalex.org/W2734601503","https://openalex.org/W2739849971","https://openalex.org/W2759385412","https://openalex.org/W2788309424","https://openalex.org/W2810219908","https://openalex.org/W2888920258","https://openalex.org/W2889098690","https://openalex.org/W2907956112","https://openalex.org/W2908833559","https://openalex.org/W2910829466","https://openalex.org/W2963212997","https://openalex.org/W2963674482","https://openalex.org/W2963840760","https://openalex.org/W2966124701","https://openalex.org/W2970568805","https://openalex.org/W3007198914","https://openalex.org/W3094003722","https://openalex.org/W3098230111","https://openalex.org/W3125626040","https://openalex.org/W3151941575","https://openalex.org/W4251465045"],"related_works":["https://openalex.org/W1759995226","https://openalex.org/W2962917430","https://openalex.org/W2040347389","https://openalex.org/W4299305030","https://openalex.org/W2952081610","https://openalex.org/W1983383464","https://openalex.org/W4299801389","https://openalex.org/W2089134982","https://openalex.org/W2028468530","https://openalex.org/W1903284337"],"abstract_inverted_index":{"Given":[0],"a":[1,5,10,62,72,94,97,101,109,156,164,177,190],"time":[2,31,63,68,87,102,135,171,184],"interval":[3,64],"and":[4,27,70,100,127,211,249],"graph":[6,73],"where":[7,20,74],"vertices":[8,122],"exhibit":[9,82,126,130],"property":[11],"of":[12,24,66,96,119,143,163,170,183,189],"interest":[13],"(PoI)":[14],"dynamically,":[15],"an":[16],"interesting":[17],"question":[18,49],"is:":[19],"(i.e.,":[21,29],"which":[22,30],"part":[23],"the":[25,34,83,114,117,131,141,161,168,181,187,216,256],"graph)":[26],"when":[28],"sub-interval)":[32],"does":[33,80],"PoI":[35,84,132],"occur":[36],"frequently?":[37],"To":[38],"our":[39,89,235],"knowledge,":[40],"no":[41,202],"work":[42],"has":[43],"been":[44],"done":[45],"to":[46,50,92,107,140,167,180,246],"answer":[47],"this":[48,54,57,124,134,144],"date.":[51],"We":[52],"address":[53],"issue":[55],"in":[56,85,123,226],"paper.":[58],"Specifically,":[59],"given":[60],"(i)":[61],"composed":[65],"multiple":[67],"slots":[69],"(ii)":[71],"each":[75,86],"vertex":[76],"either":[77],"exhibits":[78],"or":[79],"not":[81,129],"slot,":[88],"objective":[90],"is":[91,137],"find":[93],"pair":[95],"connected":[98],"sub-graph":[99,125],"sub-interval":[103,136],"(which":[104],"we":[105,147,195],"refer":[106],"as":[108],"temporal":[110],"bump),":[111],"such":[112],"that":[113,121,200],"discrepancy":[115],"between":[116],"numbers":[118],"times":[120],"do":[128],"during":[133],"maximized.":[138],"Due":[139],"NP-hardness":[142],"problem,":[145],"initially,":[146],"propose":[148,196],"two":[149,197,217],"approximation":[150,158,192,204,218],"algorithms.":[151,219],"The":[152,173],"first":[153],"one":[154,175],"achieves":[155,176],"tight":[157],"guarantee,":[159,205],"at":[160,186],"cost":[162],"weak":[165],"scalability":[166,179],"number":[169,182],"slots.":[172],"second":[174],"strong":[178],"slots,":[185],"price":[188],"loose":[191],"guarantee.":[193],"Then,":[194],"heuristic":[198],"algorithms":[199,236],"have":[201],"non-trivial":[203],"but":[206],"produce":[207],"similar":[208],"solutions":[209],"with,":[210],"are":[212,251],"considerably":[213],"faster":[214],"than,":[215],"Experiments":[220],"on":[221],"real":[222],"datasets":[223],"show":[224],"that,":[225],"comparison":[227],"with":[228,239],"baselines":[229],"built":[230],"using":[231],"related":[232],"existing":[233],"techniques,":[234],"hunt":[237],"bumps":[238],"significantly":[240],"higher":[241],"discrepancies,":[242],"while":[243],"scaling":[244],"well":[245],"large":[247],"graphs,":[248],"thus":[250],"more":[252],"suitable":[253],"for":[254],"answering":[255],"aforementioned":[257],"question.":[258]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}