{"id":"https://openalex.org/W4392849793","doi":"https://doi.org/10.1145/3650035","title":"FulBM: Fast Fully Batch Maintenance for Landmark-based 3-hop Cover Labeling","display_name":"FulBM: Fast Fully Batch Maintenance for Landmark-based 3-hop Cover Labeling","publication_year":2024,"publication_date":"2024-03-15","ids":{"openalex":"https://openalex.org/W4392849793","doi":"https://doi.org/10.1145/3650035"},"language":"en","primary_location":{"id":"doi:10.1145/3650035","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3650035","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"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 Transactions on Knowledge Discovery from Data","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/A5101968856","display_name":"Wentai Zhang","orcid":"https://orcid.org/0009-0006-3007-0554"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wentai Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0006-3007-0554","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075117055","display_name":"E Haihong","orcid":"https://orcid.org/0000-0003-2087-586X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"HaiHong E","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2087-586X","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101634508","display_name":"Haoran Luo","orcid":"https://orcid.org/0000-0003-2727-0361"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Luo","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2727-0361","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101590441","display_name":"Mingzhi Sun","orcid":"https://orcid.org/0000-0001-7967-1373"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingzhi Sun","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7967-1373","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.202,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.39814153,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"18","issue":"6","first_page":"1","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9997000098228455,"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":0.9997000098228455,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.6953291893005371},{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.6303954124450684},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5426607131958008},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5095851421356201},{"id":"https://openalex.org/keywords/hop","display_name":"Hop (telecommunications)","score":0.5014321804046631},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.49025967717170715},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.48642516136169434},{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.45224225521087646},{"id":"https://openalex.org/keywords/vertex-cover","display_name":"Vertex cover","score":0.4516708552837372},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.43123796582221985},{"id":"https://openalex.org/keywords/shortest-path-problem","display_name":"Shortest path problem","score":0.4105672538280487},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36902371048927307},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.346014142036438},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34082984924316406},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.26022326946258545},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24352240562438965},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.18051499128341675},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.08426815271377563}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6953291893005371},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.6303954124450684},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5426607131958008},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5095851421356201},{"id":"https://openalex.org/C25906391","wikidata":"https://www.wikidata.org/wiki/Q1432381","display_name":"Hop (telecommunications)","level":2,"score":0.5014321804046631},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.49025967717170715},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.48642516136169434},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.45224225521087646},{"id":"https://openalex.org/C40687702","wikidata":"https://www.wikidata.org/wiki/Q11515519","display_name":"Vertex cover","level":3,"score":0.4516708552837372},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.43123796582221985},{"id":"https://openalex.org/C22590252","wikidata":"https://www.wikidata.org/wiki/Q1058754","display_name":"Shortest path problem","level":3,"score":0.4105672538280487},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36902371048927307},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.346014142036438},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34082984924316406},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.26022326946258545},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24352240562438965},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.18051499128341675},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.08426815271377563},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3650035","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3650035","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"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 Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G697349245","display_name":null,"funder_award_id":"62176026","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321470","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W131619556","https://openalex.org/W166260623","https://openalex.org/W328847996","https://openalex.org/W1968895412","https://openalex.org/W1984336731","https://openalex.org/W2005945380","https://openalex.org/W2107884625","https://openalex.org/W2125349172","https://openalex.org/W2143083884","https://openalex.org/W2148831787","https://openalex.org/W2151078464","https://openalex.org/W2169528473","https://openalex.org/W2432978112","https://openalex.org/W2533446415","https://openalex.org/W2538876901","https://openalex.org/W2753481197","https://openalex.org/W2798620495","https://openalex.org/W2903038550","https://openalex.org/W2912491091","https://openalex.org/W2923254968","https://openalex.org/W2948227434","https://openalex.org/W2949065857","https://openalex.org/W2966124701","https://openalex.org/W2970568805","https://openalex.org/W3008629102","https://openalex.org/W3010833690","https://openalex.org/W3013028797","https://openalex.org/W3030668353","https://openalex.org/W3032255305","https://openalex.org/W3043414321","https://openalex.org/W3047022983","https://openalex.org/W3103041003","https://openalex.org/W3154936774","https://openalex.org/W3167317442","https://openalex.org/W3173430864","https://openalex.org/W3174212678","https://openalex.org/W3198197820","https://openalex.org/W3207690362","https://openalex.org/W4281719178","https://openalex.org/W4298884898","https://openalex.org/W4313143685","https://openalex.org/W4316022124"],"related_works":["https://openalex.org/W2056853153","https://openalex.org/W2057559274","https://openalex.org/W2026924879","https://openalex.org/W2005087563","https://openalex.org/W2378111931","https://openalex.org/W2052388267","https://openalex.org/W2950647290","https://openalex.org/W2620829895","https://openalex.org/W2356918560","https://openalex.org/W4243161226"],"abstract_inverted_index":{"Landmark-based":[0],"3-hop":[1,84],"cover":[2,85],"labeling":[3],"is":[4,95,116],"a":[5],"category":[6],"of":[7,48,97,158,176],"approaches":[8],"for":[9,82,124,181],"shortest":[10],"distance/path":[11,26],"queries":[12],"on":[13,40,166],"large-scale":[14],"complex":[15],"networks.":[16],"It":[17],"pre-computes":[18],"an":[19,59],"index":[20,38,49],"offline":[21],"to":[22,106,154,172,192],"accelerate":[23],"the":[24,46,74,83,89,119,132,139,156,174,197],"online":[25],"query.":[27],"Most":[28],"real-world":[29,170],"graphs":[30,42,171],"undergo":[31],"rapid":[32],"changes":[33],"in":[34,138],"topology,":[35],"which":[36,103],"makes":[37],"maintenance":[39,50,123],"dynamic":[41],"necessary.":[43],"So":[44],"far,":[45],"majority":[47],"methods":[51,189],"can":[52],"handle":[53,107],"only":[54],"one":[55],"edge":[56,109,125,136],"update":[57],"(either":[58],"addition":[60],"or":[61],"deletion)":[62],"each":[63],"time.":[64],"To":[65],"keep":[66],"up":[67],"with":[68,150,196],"frequently":[69],"changing":[70],"graphs,":[71],"we":[72],"research":[73],"ful":[75],"ly":[76],"b":[77],"atch":[78],"m":[79],"aintenance":[80],"problem":[81],"labeling,":[86],"and":[87,101,111,131,146,169,178],"proposed":[88],"method":[90],"called":[91],"FulBM":[92,94,177],".":[93],"composed":[96],"two":[98],"algorithms:":[99],"InsBM":[100,145],"DelBM,":[102],"are":[104,127,142,148],"designed":[105],"batch":[108,122],"insertions":[110,126],"deletions,":[112],"respectively.":[113],"This":[114],"separation":[115],"motivated":[117],"by":[118],"insight":[120],"that":[121,134,187],"much":[128],"more":[129],"time-efficient":[130],"fact":[133],"most":[135],"updates":[137],"real":[140],"world":[141],"incremental.":[143],"Both":[144],"DelBM":[147],"equipped":[149],"well-designed":[151],"pruning":[152],"strategies":[153],"minimize":[155],"number":[157],"vertex":[159],"accesses.":[160],"We":[161],"have":[162],"conducted":[163],"comprehensive":[164],"experiments":[165],"both":[167],"synthetic":[168],"verify":[173],"efficiency":[175],"its":[179],"variants":[180],"weighted":[182],"graphs.":[183],"The":[184],"results":[185],"show":[186],"our":[188],"achieve":[190],"5.5\u00d7":[191],"228\u00d7":[193],"speedup":[194],"compared":[195],"state-of-the-art":[198],"method.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-14T07:06:38.338062","created_date":"2025-10-10T00:00:00"}