{"id":"https://openalex.org/W2100015990","doi":"https://doi.org/10.1145/1032222.1032258","title":"A partial join approach for mining co-location patterns","display_name":"A partial join approach for mining co-location patterns","publication_year":2004,"publication_date":"2004-11-12","ids":{"openalex":"https://openalex.org/W2100015990","doi":"https://doi.org/10.1145/1032222.1032258","mag":"2100015990"},"language":"en","primary_location":{"id":"doi:10.1145/1032222.1032258","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1032222.1032258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th annual ACM international workshop on Geographic information systems","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/A5108232753","display_name":"Jin Soung Yoo","orcid":null},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jin Soung Yoo","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN","University of Minnesota , Minneapolis, Mn"],"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"University of Minnesota , Minneapolis, Mn","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102940260","display_name":"Shashi Shekhar","orcid":"https://orcid.org/0000-0002-3191-3879"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shashi Shekhar","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN","University of Minnesota , Minneapolis, Mn"],"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"University of Minnesota , Minneapolis, Mn","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103887178","display_name":"John Smith","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"John Smith","raw_affiliation_strings":["The Kumquat Consortium"],"affiliations":[{"raw_affiliation_string":"The Kumquat Consortium","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041879265","display_name":"Julius P. L. Kumquat","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Julius P. Kumquat","raw_affiliation_strings":["The Kumquat Consortium"],"affiliations":[{"raw_affiliation_string":"The Kumquat Consortium","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5108232753"],"corresponding_institution_ids":["https://openalex.org/I130238516"],"apc_list":null,"apc_paid":null,"fwci":9.4688,"has_fulltext":false,"cited_by_count":197,"citation_normalized_percentile":{"value":0.97418758,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"241","last_page":"249"},"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":0.9987000226974487,"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":0.9805999994277954,"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/join","display_name":"Join (topology)","score":0.7429948449134827},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.735826849937439},{"id":"https://openalex.org/keywords/joins","display_name":"Joins","score":0.7173144221305847},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.705444872379303},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.49767425656318665},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4567171335220337},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.4561674892902374},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.334924578666687},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.21156057715415955},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13147804141044617}],"concepts":[{"id":"https://openalex.org/C2776124973","wikidata":"https://www.wikidata.org/wiki/Q3183033","display_name":"Join (topology)","level":2,"score":0.7429948449134827},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.735826849937439},{"id":"https://openalex.org/C2778692605","wikidata":"https://www.wikidata.org/wiki/Q4041866","display_name":"Joins","level":2,"score":0.7173144221305847},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.705444872379303},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.49767425656318665},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4567171335220337},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.4561674892902374},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.334924578666687},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.21156057715415955},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13147804141044617},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1032222.1032258","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1032222.1032258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th annual ACM international workshop on Geographic information systems","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":25,"referenced_works":["https://openalex.org/W76928844","https://openalex.org/W1483679765","https://openalex.org/W1484413656","https://openalex.org/W1506285740","https://openalex.org/W1515526911","https://openalex.org/W1530753374","https://openalex.org/W1542978828","https://openalex.org/W1549255393","https://openalex.org/W1597161471","https://openalex.org/W1971318281","https://openalex.org/W1976347887","https://openalex.org/W2004951603","https://openalex.org/W2005083765","https://openalex.org/W2045487373","https://openalex.org/W2097604114","https://openalex.org/W2125233616","https://openalex.org/W2132353445","https://openalex.org/W2144402047","https://openalex.org/W2610788652","https://openalex.org/W2751199251","https://openalex.org/W6628973722","https://openalex.org/W6631977211","https://openalex.org/W6632657173","https://openalex.org/W6632759956","https://openalex.org/W6743659760"],"related_works":["https://openalex.org/W2393491644","https://openalex.org/W4206577045","https://openalex.org/W3086237447","https://openalex.org/W650102067","https://openalex.org/W1550806730","https://openalex.org/W2589740103","https://openalex.org/W2172084996","https://openalex.org/W1966967794","https://openalex.org/W1501284171","https://openalex.org/W2397450670"],"abstract_inverted_index":{"Spatial":[0],"co-location":[1,29,38,51,61,115],"patterns":[2,62],"represent":[3],"the":[4,19,23,36,73,92,106,124,146],"subsets":[5],"of":[6,26,35,49,72],"events":[7],"whose":[8],"instances":[9,48,98],"are":[10],"frequently":[11],"located":[12],"together":[13],"in":[14,22,101,112],"geographic":[15],"space.":[16],"We":[17,53,103],"identified":[18,100],"computational":[20],"bottleneck":[21],"execution":[24],"time":[25],"a":[27,55,82,87,134],"current":[28],"mining":[30,60],"algorithm.":[31,148],"A":[32],"large":[33],"fraction":[34],"join-based":[37,147],"miner":[39],"algorithm":[40,85,107,140],"is":[41,108,141],"devoted":[42],"to":[43,46],"computing":[44],"joins":[45],"identify":[47],"candidate":[50],"patterns.":[52],"propose":[54],"novel":[56],"<i>partial-join</i>":[57],"approach":[58],"for":[59,96],"efficiently.":[63],"It":[64,80],"transactionizes":[65],"continuous":[66],"spatial":[67,74],"data":[68],"while":[69],"keeping":[70],"track":[71],"information":[75],"not":[76,99],"modeled":[77],"by":[78],"transactions.":[79,102],"uses":[81],"transaction-based":[83],"<i>Apriori</i>":[84],"as":[86],"building":[88],"block":[89],"and":[90,110,120,133],"adopts":[91],"instance":[93],"join":[94],"method":[95],"residual":[97],"show":[104],"that":[105,138],"correct":[109],"complete":[111],"finding":[113],"all":[114],"rules":[116],"which":[117],"have":[118],"prevalence":[119],"conditional":[121],"probability":[122],"above":[123],"given":[125],"thresholds.":[126],"An":[127],"experimental":[128],"evaluation":[129],"using":[130],"synthetic":[131],"datasets":[132],"real":[135],"dataset":[136],"shows":[137],"our":[139],"computationally":[142],"more":[143],"efficient":[144],"than":[145]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":17},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":16},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}