{"id":"https://openalex.org/W1996909986","doi":"https://doi.org/10.1109/aiccsa.2013.6616417","title":"GCG: Mining maximal complete graph patterns from large spatial data","display_name":"GCG: Mining maximal complete graph patterns from large spatial data","publication_year":2013,"publication_date":"2013-05-01","ids":{"openalex":"https://openalex.org/W1996909986","doi":"https://doi.org/10.1109/aiccsa.2013.6616417","mag":"1996909986"},"language":"en","primary_location":{"id":"doi:10.1109/aiccsa.2013.6616417","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aiccsa.2013.6616417","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 ACS International Conference on Computer Systems and Applications (AICCSA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1312.4477","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ghazi Al-Naymat","orcid":null},"institutions":[{"id":"https://openalex.org/I76571253","display_name":"Imam Abdulrahman Bin Faisal University","ror":"https://ror.org/038cy8j79","country_code":"SA","type":"education","lineage":["https://openalex.org/I76571253"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Ghazi Al-Naymat","raw_affiliation_strings":["College of Computer Science and Information Technology, University of Dammam, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Information Technology, University of Dammam, Saudi Arabia","institution_ids":["https://openalex.org/I76571253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76571253"],"apc_list":null,"apc_paid":null,"fwci":0.8356,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.82208434,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"16","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9993000030517578,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9835000038146973,"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/graph","display_name":"Graph","score":0.5084999799728394},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.36550000309944153},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.3352000117301941},{"id":"https://openalex.org/keywords/web-mining","display_name":"Web mining","score":0.335099995136261},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.32429999113082886},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.320499986410141},{"id":"https://openalex.org/keywords/graph-database","display_name":"Graph database","score":0.3176000118255615}],"concepts":[{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5824999809265137},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.573199987411499},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5084999799728394},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37869998812675476},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.36550000309944153},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C197046077","wikidata":"https://www.wikidata.org/wiki/Q785337","display_name":"Web mining","level":3,"score":0.335099995136261},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C176225458","wikidata":"https://www.wikidata.org/wiki/Q595971","display_name":"Graph database","level":3,"score":0.3176000118255615},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2831000089645386},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C68859911","wikidata":"https://www.wikidata.org/wiki/Q1503724","display_name":"Pattern matching","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26649999618530273},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.2540999948978424},{"id":"https://openalex.org/C5737132","wikidata":"https://www.wikidata.org/wiki/Q1101814","display_name":"Clique-width","level":5,"score":0.25189998745918274},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.25110000371932983},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/aiccsa.2013.6616417","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aiccsa.2013.6616417","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 ACS International Conference on Computer Systems and Applications (AICCSA)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1312.4477","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1312.4477","pdf_url":"https://arxiv.org/pdf/1312.4477","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":null,"raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.749.3346","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.749.3346","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/1312.4477.pdf","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1312.4477","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1312.4477","pdf_url":"https://arxiv.org/pdf/1312.4477","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W198135249","https://openalex.org/W2015403588","https://openalex.org/W2097604114","https://openalex.org/W2108545961","https://openalex.org/W2123656392","https://openalex.org/W2166559705","https://openalex.org/W4252403066","https://openalex.org/W6628750762","https://openalex.org/W6653488604","https://openalex.org/W6678295487","https://openalex.org/W6684914730"],"related_works":[],"abstract_inverted_index":{"Recent":[0],"research":[1],"on":[2],"pattern":[3],"discovery":[4],"has":[5],"progressed":[6],"from":[7,113],"mining":[8,14,46,100,187],"frequent":[9,70],"patterns":[10,49,158,190],"and":[11,20,39,128],"sequences":[12],"to":[13,54,67,103,108,175],"structured":[15],"patterns,":[16],"such":[17],"as":[18,23],"trees":[19],"graphs.":[21],"Graphs":[22],"general":[24],"data":[25,32],"structure":[26],"can":[27,151],"model":[28],"complex":[29,161,188],"relations":[30],"among":[31],"with":[33],"wide":[34],"applications":[35],"in":[36,77,118,136,183,191],"web":[37],"exploration":[38],"social":[40],"networks.":[41],"However,":[42],"the":[43,55,137,164,171,177,184],"process":[44,185],"of":[45,57,60,85,139,142,166,179,186],"large":[47,58,114,140,192],"graph":[48,72,75],"is":[50,80,88,98,170],"a":[51,78,91,99,126],"challenge":[52],"due":[53],"existence":[56],"number":[59,141],"subgraphs.":[61],"In":[62,144],"this":[63,145,169],"paper,":[64,146],"we":[65,147],"aim":[66],"mine":[68,152],"only":[69,154],"complete":[71,81,111,181],"patterns.":[73,143],"A":[74],"g":[76],"database":[79],"if":[82],"every":[83],"pair":[84],"distinct":[86],"vertices":[87],"connected":[89],"by":[90],"unique":[92],"edge.":[93],"Grid":[94],"Complete":[95],"Graph":[96],"(GCG)":[97],"algorithm":[101,173],"developed":[102],"explore":[104],"interesting":[105],"pruning":[106],"techniques":[107],"extract":[109],"maximal":[110,180],"graphs":[112,182],"spatial":[115,157,193],"dataset":[116],"existing":[117],"Sloan":[119],"Digital":[120],"Sky":[121],"Survey":[122],"(SDSS)":[123],"data.":[124],"Using":[125],"divide":[127],"conquer":[129],"strategy,":[130],"GCG":[131,149],"shows":[132],"high":[133],"efficiency":[134],"especially":[135],"presence":[138],"describe":[148],"that":[150],"not":[153],"simple":[155],"co-location":[156,189],"but":[159],"also":[160],"ones.":[162],"To":[163],"best":[165],"our":[167],"knowledge,":[168],"first":[172],"used":[174],"exploit":[176],"extraction":[178],"dataset.":[194]},"counts_by_year":[{"year":2014,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
