{"id":"https://openalex.org/W4403582565","doi":"https://doi.org/10.1145/3627673.3679865","title":"<scp>GetCom</scp> : An Efficient and Generalizable Framework for Community Detection","display_name":"<scp>GetCom</scp> : An Efficient and Generalizable Framework for Community Detection","publication_year":2024,"publication_date":"2024-10-20","ids":{"openalex":"https://openalex.org/W4403582565","doi":"https://doi.org/10.1145/3627673.3679865"},"language":"en","primary_location":{"id":"doi:10.1145/3627673.3679865","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627673.3679865","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","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/A5015160679","display_name":"Kaiyu Xiong","orcid":"https://orcid.org/0009-0000-1719-7127"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kaiyu Xiong","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University Shanghai, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University Shanghai, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085646235","display_name":"Yucheng Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yucheng Jin","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University Shanghai, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University Shanghai, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001877137","display_name":"Yun Xiong","orcid":"https://orcid.org/0000-0002-8575-5415"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Xiong","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University Shanghai, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University Shanghai, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100462824","display_name":"Jiawei Zhang","orcid":"https://orcid.org/0000-0002-2111-7617"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiawei Zhang","raw_affiliation_strings":["IFM Lab, Department of Computer Science, University of California, Davis, CA, USA"],"affiliations":[{"raw_affiliation_string":"IFM Lab, Department of Computer Science, University of California, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5015160679"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.5891,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66535633,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2650","last_page":"2659"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9993000030517578,"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":0.9993000030517578,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9914000034332275,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.6711595058441162},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.36748796701431274}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6711595058441162},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.36748796701431274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3627673.3679865","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627673.3679865","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","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":28,"referenced_works":["https://openalex.org/W1971421925","https://openalex.org/W2111002549","https://openalex.org/W2119998616","https://openalex.org/W2127048411","https://openalex.org/W2131681506","https://openalex.org/W2132202037","https://openalex.org/W2139694940","https://openalex.org/W2140000690","https://openalex.org/W2157085604","https://openalex.org/W2169148563","https://openalex.org/W2327762824","https://openalex.org/W2411855254","https://openalex.org/W2547646153","https://openalex.org/W2562998547","https://openalex.org/W2767849480","https://openalex.org/W2788730644","https://openalex.org/W2907760765","https://openalex.org/W2949559065","https://openalex.org/W3080668436","https://openalex.org/W3099768174","https://openalex.org/W3102641634","https://openalex.org/W3164338400","https://openalex.org/W3185341429","https://openalex.org/W4290877635","https://openalex.org/W4367046738","https://openalex.org/W4367046771","https://openalex.org/W4383468961","https://openalex.org/W4385565193"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Community":[0],"detection":[1,95],"plays":[2],"a":[3,54,82],"pivotal":[4],"role":[5],"in":[6,11,27,108],"network":[7,33,129],"analysis,":[8],"with":[9,137],"applications":[10],"recommendation":[12],"systems,":[13],"anomaly":[14],"detection,":[15],"and":[16,47,65,119,140,146],"biochemistry.":[17],"However,":[18],"traditional":[19,63,93],"methods,":[20],"while":[21],"computationally":[22],"efficient,":[23,117],"often":[24],"fall":[25],"short":[26],"managing":[28],"the":[29,70,86,90,109],"complexities":[30],"of":[31,77],"real-world":[32,128],"structures.":[34],"In":[35,69],"contrast,":[36],"deep":[37,66],"learning":[38,67,111],"approaches":[39],"enhance":[40],"accuracy":[41],"but":[42],"require":[43],"substantial":[44],"computational":[45],"resources":[46],"task-specific":[48],"architectures.":[49],"This":[50,113],"paper":[51],"introduce":[52],"GetCom,":[53],"novel":[55],"three-phase":[56],"\"pre-train,":[57],"generate,":[58],"prompt\"":[59],"framework":[60],"that":[61,132],"integrates":[62],"methods":[64,96],"techniques.":[68],"pre-training":[71],"phase,":[72,92],"GetCom":[73,133],"acquires":[74],"comprehensive":[75],"understanding":[76],"community":[78,94,123],"structures,":[79],"which":[80,104],"provides":[81],"solid":[83],"foundation":[84],"for":[85,122],"subsequent":[87],"phases.":[88],"During":[89],"generation":[91],"are":[97,105],"employed":[98],"to":[99],"efficiently":[100],"identify":[101],"potential":[102],"communities,":[103],"subsequently":[106],"refined":[107],"prompt":[110],"phase.":[112],"integration":[114],"offers":[115],"an":[116],"accurate,":[118],"generalizable":[120],"solution":[121],"detection.":[124],"Experiments":[125],"on":[126],"five":[127],"datasets":[130,145],"demonstrate":[131],"achieves":[134],"state-of-the-art":[135],"performance,":[136],"strong":[138],"efficiency":[139],"generalization":[141],"capabilities":[142],"across":[143],"diverse":[144],"tasks.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
