{"id":"https://openalex.org/W2786342288","doi":"https://doi.org/10.1145/3195635","title":"Updating Dynamic Random Hyperbolic Graphs in Sublinear Time","display_name":"Updating Dynamic Random Hyperbolic Graphs in Sublinear Time","publication_year":2018,"publication_date":"2018-11-15","ids":{"openalex":"https://openalex.org/W2786342288","doi":"https://doi.org/10.1145/3195635","mag":"2786342288"},"language":"en","primary_location":{"id":"doi:10.1145/3195635","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3195635","pdf_url":null,"source":{"id":"https://openalex.org/S201104086","display_name":"ACM Journal of Experimental Algorithmics","issn_l":"1084-6654","issn":["1084-6654"],"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 Journal of Experimental Algorithmics","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1802.03297","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040876329","display_name":"Moritz von Looz","orcid":"https://orcid.org/0000-0001-5697-7142"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Moritz Von Looz","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT), Cologne, Germany"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT), Cologne, Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020196859","display_name":"Henning Meyerhenke","orcid":"https://orcid.org/0000-0002-7769-726X"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Henning Meyerhenke","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT), Cologne, Germany"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT), Cologne, Germany","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5040876329"],"corresponding_institution_ids":["https://openalex.org/I102335020"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01169094,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"23","issue":null,"first_page":"1","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9839000105857849,"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"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9839000105857849,"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"}},{"id":"https://openalex.org/T11896","display_name":"Opportunistic and Delay-Tolerant Networks","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11152","display_name":"Stochastic processes and statistical mechanics","score":0.979200005531311,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperbolic-geometry","display_name":"Hyperbolic geometry","score":0.656493067741394},{"id":"https://openalex.org/keywords/sublinear-function","display_name":"Sublinear function","score":0.6389113664627075},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6341807842254639},{"id":"https://openalex.org/keywords/random-graph","display_name":"Random graph","score":0.5354772806167603},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.48959881067276},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.4714411497116089},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.456259548664093},{"id":"https://openalex.org/keywords/hyperbolic-tree","display_name":"Hyperbolic tree","score":0.41638684272766113},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3514097332954407},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.32599979639053345}],"concepts":[{"id":"https://openalex.org/C206352148","wikidata":"https://www.wikidata.org/wiki/Q209306","display_name":"Hyperbolic geometry","level":3,"score":0.656493067741394},{"id":"https://openalex.org/C117160843","wikidata":"https://www.wikidata.org/wiki/Q338652","display_name":"Sublinear function","level":2,"score":0.6389113664627075},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6341807842254639},{"id":"https://openalex.org/C47458327","wikidata":"https://www.wikidata.org/wiki/Q910404","display_name":"Random graph","level":3,"score":0.5354772806167603},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.48959881067276},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.4714411497116089},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.456259548664093},{"id":"https://openalex.org/C97654310","wikidata":"https://www.wikidata.org/wiki/Q574023","display_name":"Hyperbolic tree","level":4,"score":0.41638684272766113},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3514097332954407},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.32599979639053345},{"id":"https://openalex.org/C192939610","wikidata":"https://www.wikidata.org/wiki/Q188444","display_name":"Differential geometry","level":2,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3195635","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3195635","pdf_url":null,"source":{"id":"https://openalex.org/S201104086","display_name":"ACM Journal of Experimental Algorithmics","issn_l":"1084-6654","issn":["1084-6654"],"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 Journal of Experimental Algorithmics","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1802.03297","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1802.03297","pdf_url":"https://arxiv.org/pdf/1802.03297","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2786342288","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1802.03297","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1802.03297","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1802.03297","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1802.03297","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1802.03297","pdf_url":"https://arxiv.org/pdf/1802.03297","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5699999928474426}],"awards":[{"id":"https://openalex.org/G6052429835","display_name":null,"funder_award_id":"(DFG)","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G8224790471","display_name":null,"funder_award_id":"ME 3619/3-1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W2786342288.pdf"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W614478005","https://openalex.org/W1971215074","https://openalex.org/W1991834433","https://openalex.org/W2008006577","https://openalex.org/W2028314260","https://openalex.org/W2049075975","https://openalex.org/W2059355691","https://openalex.org/W2085761620","https://openalex.org/W2152948207","https://openalex.org/W2158194525","https://openalex.org/W2182516227","https://openalex.org/W2223638254","https://openalex.org/W2271510144","https://openalex.org/W2284958355","https://openalex.org/W2401915092","https://openalex.org/W2899702797","https://openalex.org/W2950563475","https://openalex.org/W2963017687","https://openalex.org/W2963794747","https://openalex.org/W2963982460","https://openalex.org/W4233413206","https://openalex.org/W4238452917"],"related_works":["https://openalex.org/W3099643767","https://openalex.org/W2795470862","https://openalex.org/W2243241072","https://openalex.org/W2406266674","https://openalex.org/W2400041466","https://openalex.org/W2782820392","https://openalex.org/W2951038604","https://openalex.org/W2742748487","https://openalex.org/W2952104302","https://openalex.org/W1950779386","https://openalex.org/W3202628225","https://openalex.org/W2964120271","https://openalex.org/W2085336826","https://openalex.org/W1537954077","https://openalex.org/W2736040825","https://openalex.org/W2025809050","https://openalex.org/W3042194019","https://openalex.org/W3088419579","https://openalex.org/W2272441262","https://openalex.org/W3102249523"],"abstract_inverted_index":{"Generative":[0],"network":[1,12,24,66],"models":[2],"play":[3],"an":[4],"important":[5],"role":[6],"in":[7,40,100,199,227,231,235,244],"algorithm":[8,175,195,257],"development,":[9],"scaling":[10],"studies,":[11],"analysis,":[13],"and":[14,44,113,147],"realistic":[15],"system":[16],"benchmarks":[17],"for":[18,269],"graph":[19],"data":[20],"sets.":[21,183],"A":[22],"complex":[23],"model":[25,64],"gaining":[26],"considerable":[27],"popularity":[28],"builds":[29],"random":[30,143,228],"hyperbolic":[31,42,56,103,229],"graphs,":[32],"generated":[33],"by":[34],"distributing":[35],"points":[36,49,99],"within":[37],"a":[38,51,60,88,95,106,110,121,142,171,197,224,236],"disk":[39],"the":[41,73,79,85,126,248],"plane":[43],"then":[45],"adding":[46],"edges":[47],"between":[48],"with":[50,137,161,216],"probability":[52,162],"depending":[53],"on":[54],"their":[55],"distance.":[57],"We":[58,169],"present":[59,170],"dynamic":[61,80],"extension":[62],"to":[63,139,154,176,222,247,261],"gradual":[65],"change,":[67],"while":[68],"preserving":[69],"at":[70],"each":[71,148],"step":[72],"point":[74,149,182],"position":[75],"probabilities.":[76],"To":[77],"process":[78,223],"changes":[81],"efficiently,":[82],"we":[83,191],"formalize":[84],"concept":[86],"of":[87,97,135,145,187,238,242,266],"probabilistic":[89,127,178,273],"neighborhood":[90,128],":":[91,115],"Let":[92],"P":[93,146,152,189],"be":[94],"set":[96],"n":[98,210,213],"Euclidean":[101,262],"or":[102,272],"space,":[104],"q":[105,131,136,157,167,204],"query":[107,174,198,256],"point,":[108],"dist":[109],"distance":[111],"metric,":[112],"f":[114,133,140,159,163,206],"R":[116],"+":[117,208],"\u2192":[118],"[0,":[119],"1]":[120],"monotonically":[122],"decreasing":[123],"function.":[124],"Then,":[125],"N":[129,155,202],"(":[130,156,203],",":[132,158,166,190,205],")":[134,160,211,214],"respect":[138],"is":[141,258],"subset":[144],"p":[150,165],"\u2208":[151],"belongs":[153],"(dist(":[164],")).":[168],"fast,":[172],"sublinear-time":[173],"sample":[177],"neighborhoods":[179],"from":[180,253],"planar":[181,188],"For":[184],"certain":[185],"distributions":[186],"prove":[192],"that":[193],"our":[194,255],"answers":[196],"O":[200],"((|":[201],")|":[207],"\u221a":[209],"log":[212],"time":[215],"high":[217],"probability.":[218],"This":[219],"enables":[220],"us":[221],"node":[225],"movement":[226],"graphs":[230],"sublinear":[232],"time,":[233],"resulting":[234],"speedup":[237],"about":[239],"one":[240],"order":[241],"magnitude":[243],"practice":[245],"compared":[246],"fastest":[249],"previous":[250],"approach.":[251],"Apart":[252],"that,":[254],"also":[259],"applicable":[260],"geometry,":[263],"making":[264],"it":[265],"independent":[267],"interest":[268],"other":[270],"sampling":[271],"spreading":[274],"scenarios.":[275]},"counts_by_year":[],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}