{"id":"https://openalex.org/W3199680928","doi":"https://doi.org/10.1145/3460418.3480412","title":"Data-driven Clustering in Ad-hoc Networks based on Community Detection","display_name":"Data-driven Clustering in Ad-hoc Networks based on Community Detection","publication_year":2021,"publication_date":"2021-09-21","ids":{"openalex":"https://openalex.org/W3199680928","doi":"https://doi.org/10.1145/3460418.3480412","mag":"3199680928"},"language":"en","primary_location":{"id":"doi:10.1145/3460418.3480412","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460418.3480412","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers","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/A5084634507","display_name":"Shufan Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shufan Huang","raw_affiliation_strings":["Shanghai JiaoTong University, China"],"affiliations":[{"raw_affiliation_string":"Shanghai JiaoTong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065362219","display_name":"Yongpeng Wu","orcid":"https://orcid.org/0000-0001-8210-5057"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongpeng Wu","raw_affiliation_strings":["Shanghai Jiao Tong University, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089561890","display_name":"Siyuan Gao","orcid":"https://orcid.org/0000-0002-8925-7042"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siyuan Gao","raw_affiliation_strings":["Jiangxi Institute of Metrology &amp; Testing, China"],"affiliations":[{"raw_affiliation_string":"Jiangxi Institute of Metrology &amp; Testing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5084634507"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.2625,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.54849691,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"631","last_page":"636"},"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/T11896","display_name":"Opportunistic and Delay-Tolerant Networks","score":0.9983999729156494,"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/T10246","display_name":"Mobile Ad Hoc Networks","score":0.9979000091552734,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8270868062973022},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7988108396530151},{"id":"https://openalex.org/keywords/wireless-ad-hoc-network","display_name":"Wireless ad hoc network","score":0.727072536945343},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5398082137107849},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5328781008720398},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4265550971031189},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4192308783531189},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.41444098949432373},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3646761476993561},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.35374993085861206},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.312740683555603},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2682373821735382},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.20476070046424866},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.0914556086063385}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8270868062973022},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7988108396530151},{"id":"https://openalex.org/C94523657","wikidata":"https://www.wikidata.org/wiki/Q4085781","display_name":"Wireless ad hoc network","level":3,"score":0.727072536945343},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5398082137107849},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5328781008720398},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4265550971031189},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4192308783531189},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.41444098949432373},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3646761476993561},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.35374993085861206},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.312740683555603},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2682373821735382},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.20476070046424866},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0914556086063385},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3460418.3480412","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460418.3480412","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5495080709","display_name":null,"funder_award_id":"2018YFB1801102","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G7724135216","display_name":null,"funder_award_id":"62071289","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1971421925","https://openalex.org/W1981891377","https://openalex.org/W2045349136","https://openalex.org/W2053568252","https://openalex.org/W2062825488","https://openalex.org/W2082674813","https://openalex.org/W2089458547","https://openalex.org/W2101678493","https://openalex.org/W2119571791","https://openalex.org/W2124209874","https://openalex.org/W2131681506","https://openalex.org/W2132202037","https://openalex.org/W2145872061","https://openalex.org/W2149076393","https://openalex.org/W2291036501","https://openalex.org/W2583143836","https://openalex.org/W2626759838","https://openalex.org/W2803531409","https://openalex.org/W2940896719","https://openalex.org/W2952609329","https://openalex.org/W3093301018","https://openalex.org/W3099768174"],"related_works":["https://openalex.org/W2366107444","https://openalex.org/W4388145910","https://openalex.org/W1976205134","https://openalex.org/W2381570729","https://openalex.org/W4248336175","https://openalex.org/W3009369890","https://openalex.org/W2031260042","https://openalex.org/W2391445434","https://openalex.org/W4312490297","https://openalex.org/W2062212388"],"abstract_inverted_index":{"High":[0],"demands":[1,17],"for":[2,18,30,103],"industrial":[3],"networks":[4,15,32,65],"lead":[5],"to":[6,40,73,88],"increasingly":[7],"large":[8],"sensor":[9],"networks.":[10,61],"However,":[11],"the":[12,83,113],"complexity":[13],"of":[14,85,115],"and":[16,24,37,44,58,68,132],"accurate":[19],"data":[20],"require":[21],"better":[22],"stability":[23,131],"communication":[25,46],"quality.":[26,47,133],"Conventional":[27],"clustering":[28,42],"methods":[29,72],"ad-hoc":[31,60,64],"are":[33],"based":[34],"on":[35,53,120],"topology":[36],"connectivity,":[38],"leading":[39],"unstable":[41],"results":[43,84,114],"low":[45],"In":[48,106],"this":[49],"paper,":[50],"we":[51,97,109],"focus":[52],"two":[54],"situations:":[55],"time-evolving":[56,78],"networks,":[57,79,108],"multi-channel":[59,107],"We":[62],"model":[63],"as":[66],"graphs":[67],"introduce":[69],"community":[70,86,117],"detection":[71,87],"both":[74,130],"situations.":[75],"Particularly,":[76],"in":[77,129],"our":[80,125],"method":[81,126],"utilizes":[82],"ensure":[89],"stability.":[90],"By":[91],"using":[92],"similarity":[93],"or":[94],"human-in-the-loop":[95],"measures,":[96],"construct":[98],"a":[99],"new":[100],"weighted":[101],"graph":[102],"final":[104],"clustering.":[105],"perform":[110],"allocations":[111],"from":[112],"multiplex":[116],"detection.":[118],"Experiments":[119],"real-world":[121],"datasets":[122],"show":[123],"that":[124],"outperforms":[127],"baselines":[128]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}
