{"id":"https://openalex.org/W3107587529","doi":"https://doi.org/10.1145/3397536.3422217","title":"Discovering Spatial Mixture Patterns of Interest","display_name":"Discovering Spatial Mixture Patterns of Interest","publication_year":2020,"publication_date":"2020-11-03","ids":{"openalex":"https://openalex.org/W3107587529","doi":"https://doi.org/10.1145/3397536.3422217","mag":"3107587529"},"language":"en","primary_location":{"id":"doi:10.1145/3397536.3422217","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397536.3422217","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th International Conference on Advances in 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/A5049041437","display_name":"Yiqun Xie","orcid":"https://orcid.org/0000-0002-6439-1333"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yiqun Xie","raw_affiliation_strings":["University of Maryland"],"affiliations":[{"raw_affiliation_string":"University of Maryland","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050161940","display_name":"Han Bao","orcid":"https://orcid.org/0000-0002-0109-8260"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Han Bao","raw_affiliation_strings":["University of Iowa"],"affiliations":[{"raw_affiliation_string":"University of Iowa","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380410","display_name":"Yan Li","orcid":"https://orcid.org/0000-0003-0703-1689"},"institutions":[{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Li","raw_affiliation_strings":["University of Minnesota"],"affiliations":[{"raw_affiliation_string":"University of Minnesota","institution_ids":["https://openalex.org/I2800403580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037233397","display_name":"Shashi Shekhar","orcid":"https://orcid.org/0000-0001-8837-192X"},"institutions":[{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shashi Shekhar","raw_affiliation_strings":["University of Minnesota"],"affiliations":[{"raw_affiliation_string":"University of Minnesota","institution_ids":["https://openalex.org/I2800403580"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5049041437"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":1.013,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.78044151,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"608","last_page":"617"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10877","display_name":"Allergic Rhinitis and Sensitization","score":0.9556999802589417,"subfield":{"id":"https://openalex.org/subfields/2723","display_name":"Immunology and Allergy"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9156000018119812,"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/computer-science","display_name":"Computer science","score":0.683704137802124},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6443583965301514},{"id":"https://openalex.org/keywords/randomness","display_name":"Randomness","score":0.5161150693893433},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4973278343677521},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.45041391253471375},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.43607741594314575},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4312480390071869},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.42709779739379883},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3897114396095276},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.355479896068573},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21432378888130188},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1923588216304779}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.683704137802124},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6443583965301514},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.5161150693893433},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4973278343677521},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.45041391253471375},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.43607741594314575},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4312480390071869},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.42709779739379883},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3897114396095276},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.355479896068573},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21432378888130188},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1923588216304779},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3397536.3422217","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397536.3422217","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G2729580444","display_name":null,"funder_award_id":"1737633,1901099","funder_id":"https://openalex.org/F4320309085","funder_display_name":"Center for Selective C-H Functionalization, National Science Foundation"},{"id":"https://openalex.org/G7112848026","display_name":null,"funder_award_id":"2017-51181-27222","funder_id":"https://openalex.org/F4320306114","funder_display_name":"U.S. Department of Agriculture"}],"funders":[{"id":"https://openalex.org/F4320306114","display_name":"U.S. Department of Agriculture","ror":"https://ror.org/01na82s61"},{"id":"https://openalex.org/F4320309085","display_name":"Center for Selective C-H Functionalization, National Science Foundation","ror":"https://ror.org/02h8v7m77"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1990158612","https://openalex.org/W2030822855","https://openalex.org/W2037223867","https://openalex.org/W2065082780","https://openalex.org/W2070822608","https://openalex.org/W2083772019","https://openalex.org/W2109119832","https://openalex.org/W2110845589","https://openalex.org/W2434386361","https://openalex.org/W2907893404","https://openalex.org/W2967908858","https://openalex.org/W2989250569","https://openalex.org/W4214673296","https://openalex.org/W4233192639"],"related_works":["https://openalex.org/W3034924094","https://openalex.org/W3094954546","https://openalex.org/W1488708774","https://openalex.org/W2981906196","https://openalex.org/W1982811510","https://openalex.org/W4391100477","https://openalex.org/W4327779705","https://openalex.org/W1513698804","https://openalex.org/W4310560702","https://openalex.org/W2029712093"],"abstract_inverted_index":{"Given":[0],"a":[1,150,164,170,186],"collection":[2],"of":[3,8,18,23,34,36,51,69,79,87,102,118,132],"N":[4],"geo-located":[5],"point":[6],"samples":[7],"k":[9],"types,":[10],"we":[11,147,162,179],"aim":[12],"to":[13,76,108,115,139,154,190],"detect":[14,209],"spatial":[15,140,151,174],"mixture":[16,33,40,89,106,119,152,175,210],"patterns":[17,41,71,120,211],"interest,":[19],"which":[20],"are":[21,136],"sub-regions":[22],"the":[24,77,94,116,134,145,192,205,216],"study":[25],"area":[26],"that":[27,204],"have":[28,42],"significantly":[29],"high":[30,103,113,213,226],"or":[31,104],"low":[32,105],"points":[35],"different":[37],"types.":[38],"Spatial":[39],"important":[43],"applications":[44],"in":[45,121,127],"many":[46],"societal":[47],"domains,":[48],"including":[49],"resilience":[50],"smart":[52],"cities":[53],"and":[54,67,82,112,185,200,215],"communities,":[55],"biodiversity,":[56],"equity,":[57],"business":[58],"intelligence,":[59],"etc.":[60],"The":[61],"problem":[62],"is":[63],"challenging":[64],"because":[65],"ranking":[66,157],"selection":[68],"candidate":[70,159],"can":[72,208,219],"be":[73],"highly":[74],"susceptible":[75],"effect":[78],"natural":[80],"randomness,":[81],"real-world":[83,201],"data":[84,202],"often":[85],"consists":[86],"various":[88],"patterns.":[90,160],"In":[91],"related":[92],"work,":[93],"multi-nomial":[95],"scan":[96],"statistic":[97],"does":[98],"not":[99],"support":[100],"identification":[101],"due":[107],"its":[109],"\"directionless\"":[110],"nature":[111],"sensitivity":[114],"composition":[117],"data.":[122],"While":[123],"species":[124],"richness":[125],"indices":[126],"biodiversity":[128],"research":[129],"allow":[130],"specification":[131],"directions,":[133],"measures":[135],"very":[137],"sensitive":[138],"randomness":[141],"effects.":[142],"To":[143],"bridge":[144],"gap,":[146],"first":[148],"propose":[149,180],"index":[153],"provide":[155],"robust":[156],"among":[158],"Then,":[161],"present":[163],"dual-level":[165],"Monte-Carlo":[166],"estimation":[167],"method":[168],"with":[169,197,212],"baseline":[171,193],"algorithm":[172,184],"for":[173],"pattern":[176],"detection.":[177],"Finally,":[178],"both":[181,198],"an":[182],"exact":[183],"distribution-inspired":[187],"sequence-reduction":[188],"heuristic":[189],"accelerate":[191],"approach.":[194],"Experiment":[195],"results":[196],"synthetic":[199],"show":[203],"proposed":[206],"approaches":[207],"accuracy,":[214],"acceleration":[217],"methods":[218],"greatly":[220],"reduce":[221],"computational":[222],"cost":[223],"while":[224],"maintaining":[225],"solution":[227],"quality.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
