{"id":"https://openalex.org/W4407694712","doi":"https://doi.org/10.14778/3704965.3704981","title":"Topology-Preserving Graph Coarsening: An Elementary Collapse-Based Approach","display_name":"Topology-Preserving Graph Coarsening: An Elementary Collapse-Based Approach","publication_year":2024,"publication_date":"2024-09-01","ids":{"openalex":"https://openalex.org/W4407694712","doi":"https://doi.org/10.14778/3704965.3704981"},"language":"en","primary_location":{"id":"doi:10.14778/3704965.3704981","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3704965.3704981","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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":"Proceedings of the VLDB Endowment","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/A5111195233","display_name":"Yuchen Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuchen Meng","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100742464","display_name":"Rong-Hua Li","orcid":"https://orcid.org/0000-0001-8658-6599"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong-Hua Li","raw_affiliation_strings":["Key Laboratory of Intelligent Supply Chain Technology, Shenzhen, China and Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Supply Chain Technology, Shenzhen, China and Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101021504","display_name":"Longlong Lin","orcid":"https://orcid.org/0000-0002-2194-8146"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longlong Lin","raw_affiliation_strings":["Southwest University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028148241","display_name":"Xunkai Li","orcid":"https://orcid.org/0000-0002-1230-7603"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xunkai Li","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054991337","display_name":"Guoren Wang","orcid":"https://orcid.org/0000-0002-0181-8379"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoren Wang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2262,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.81206099,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"17","issue":"13","first_page":"4760","last_page":"4772"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9997000098228455,"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9976999759674072,"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/topology","display_name":"Topology (electrical circuits)","score":0.6639454364776611},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4996044635772705},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4336429834365845},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.34573882818222046},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.21086403727531433}],"concepts":[{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.6639454364776611},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4996044635772705},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4336429834365845},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.34573882818222046},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.21086403727531433}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14778/3704965.3704981","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3704965.3704981","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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":"Proceedings of the VLDB Endowment","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1490949485","https://openalex.org/W1567562836","https://openalex.org/W1583837637","https://openalex.org/W1968537206","https://openalex.org/W1999446611","https://openalex.org/W2022322548","https://openalex.org/W2118953734","https://openalex.org/W2486762503","https://openalex.org/W2558460151","https://openalex.org/W2945827377","https://openalex.org/W3039500550","https://openalex.org/W3101543043","https://openalex.org/W3101553402","https://openalex.org/W3172620719","https://openalex.org/W4213033583","https://openalex.org/W4213378996","https://openalex.org/W4318812488","https://openalex.org/W4382240020","https://openalex.org/W4394685238","https://openalex.org/W4396601642","https://openalex.org/W4399419059","https://openalex.org/W6629511120"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4391375266","https://openalex.org/W1979597421","https://openalex.org/W2007980826","https://openalex.org/W2061531152","https://openalex.org/W3002753104","https://openalex.org/W2077600819","https://openalex.org/W2142036596","https://openalex.org/W2072657027"],"abstract_inverted_index":{"Graph":[0,67],"coarsening":[1,32,64,104],"techniques":[2,33,126],"aim":[3],"at":[4],"simplifying":[5],"the":[6,14,73,100,103,118,129,144],"graph":[7,23,26,31,40,54,63,82,101],"structure":[8],"while":[9],"preserving":[10,37,53,107],"key":[11],"properties":[12],"in":[13,22,78],"resulting":[15],"coarsened":[16],"graph,":[17],"have":[18],"been":[19],"widely":[20],"used":[21],"partitioning":[24],"and":[25,114,131,146],"neural":[27],"networks":[28],"(GNNs).":[29],"Existing":[30],"mainly":[34],"focus":[35],"on":[36,52,139],"cuts":[38],"or":[39],"spectrums.":[41],"In":[42,57],"this":[43,85],"paper,":[44],"we":[45,59,88,120],"propose":[46,122],"a":[47,61,91],"new":[48],"method":[49,151],"that":[50],"focuses":[51],"topological":[55,109],"features.":[56],"particular,":[58],"develop":[60],"novel":[62,86],"approach,":[65],"called":[66,96],"Elementary":[68],"Collapse":[69],"(GEC),":[70],"by":[71],"extending":[72],"concept":[74],"of":[75,93,99,134,148],"elementary":[76],"collapse":[77],"algebraic":[79],"topology":[80],"to":[81,127],"analysis.":[83],"With":[84],"method,":[87],"can":[89],"ensure":[90],"kind":[92],"equivalence":[94,98],"relationship":[95],"homotopy":[97],"during":[102],"process,":[105],"thereby":[106],"numerous":[108],"properties,":[110],"including":[111],"connectivity,":[112],"rings,":[113],"voids.":[115],"To":[116],"enhance":[117],"scalability,":[119],"also":[121],"several":[123,140],"carefully-designed":[124],"optimization":[125],"reduce":[128],"time":[130],"memory":[132],"consumption":[133],"our":[135,149],"approach.":[136],"Extensive":[137],"experiments":[138],"real-world":[141],"datasets":[142],"demonstrate":[143],"effectiveness":[145],"efficiency":[147],"proposed":[150],"across":[152],"various":[153],"GNN":[154],"prediction":[155],"tasks.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
