{"id":"https://openalex.org/W2096793442","doi":"https://doi.org/10.1109/icdm.2003.1250986","title":"Algorithms for spatial outlier detection","display_name":"Algorithms for spatial outlier detection","publication_year":2004,"publication_date":"2004-04-23","ids":{"openalex":"https://openalex.org/W2096793442","doi":"https://doi.org/10.1109/icdm.2003.1250986","mag":"2096793442"},"language":"en","primary_location":{"id":"doi:10.1109/icdm.2003.1250986","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250986","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","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/A5038002204","display_name":"Chang\u2010Tien Lu","orcid":"https://orcid.org/0000-0003-3675-0199"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"C.-T. Lu","raw_affiliation_strings":["Department of Computer Science, Virginia Polytechnic Institute and State University, Falls Church, VA, USA","Dept. of Comput. Sci., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Virginia Polytechnic Institute and State University, Falls Church, VA, USA","institution_ids":["https://openalex.org/I859038795"]},{"raw_affiliation_string":"Dept. of Comput. Sci., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050077196","display_name":"Dechang Chen","orcid":"https://orcid.org/0000-0001-5787-3441"},"institutions":[{"id":"https://openalex.org/I148314036","display_name":"Uniformed Services University of the Health Sciences","ror":"https://ror.org/04r3kq386","country_code":"US","type":"education","lineage":["https://openalex.org/I148314036"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D. Chen","raw_affiliation_strings":["Preventive Medicine and Biometrics, Uniformed Services University of Health Sciences, Bethesda, MD, USA","Uniformed Services University of the Health Sciences; Bethesda MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Preventive Medicine and Biometrics, Uniformed Services University of Health Sciences, Bethesda, MD, USA","institution_ids":["https://openalex.org/I148314036"]},{"raw_affiliation_string":"Uniformed Services University of the Health Sciences; Bethesda MD","institution_ids":["https://openalex.org/I148314036"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101761165","display_name":"Yang-Yang Kou","orcid":"https://orcid.org/0009-0004-3702-832X"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Y. Kou","raw_affiliation_strings":["Department of Computer Science, Virginia Polytechnic Institute and State University, Falls Church, VA, USA","Virginia Polytechnic Institute and State Univ., Falls Church#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Virginia Polytechnic Institute and State University, Falls Church, VA, USA","institution_ids":["https://openalex.org/I859038795"]},{"raw_affiliation_string":"Virginia Polytechnic Institute and State Univ., Falls Church#TAB#","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.9531,"has_fulltext":false,"cited_by_count":153,"citation_normalized_percentile":{"value":0.98653358,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"597","last_page":"600"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9947999715805054,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.8903318047523499},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7434558272361755},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6901209354400635},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5659374594688416},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5482407808303833},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48228004574775696},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4631921648979187},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4623734951019287},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4349171221256256},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.41101276874542236},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2299836277961731},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16186562180519104}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.8903318047523499},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7434558272361755},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6901209354400635},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5659374594688416},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5482407808303833},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48228004574775696},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4631921648979187},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4623734951019287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4349171221256256},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41101276874542236},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2299836277961731},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16186562180519104},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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:10.1109/icdm.2003.1250986","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250986","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6299999952316284,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W204779855","https://openalex.org/W1552339598","https://openalex.org/W1586410151","https://openalex.org/W1903475782","https://openalex.org/W1970655212","https://openalex.org/W1971812279","https://openalex.org/W2004675752","https://openalex.org/W2035006576","https://openalex.org/W2049058890","https://openalex.org/W2057117782","https://openalex.org/W2066098405","https://openalex.org/W2108495858","https://openalex.org/W2112440119","https://openalex.org/W2118898434","https://openalex.org/W2186258832","https://openalex.org/W2316627393","https://openalex.org/W2331052961","https://openalex.org/W4242253078","https://openalex.org/W4243367259","https://openalex.org/W4301773902","https://openalex.org/W6608289497","https://openalex.org/W6632829031"],"related_works":["https://openalex.org/W2359185137","https://openalex.org/W2186522517","https://openalex.org/W2090668960","https://openalex.org/W2172289703","https://openalex.org/W3152110224","https://openalex.org/W4230206970","https://openalex.org/W2030388591","https://openalex.org/W2189033663","https://openalex.org/W2899229695","https://openalex.org/W2051290323"],"abstract_inverted_index":{"A":[0],"spatial":[1,23,35,55,62,69,80,95,116,122],"outlier":[2,70,81],"is":[3,45],"a":[4,66,85,100],"spatially":[5],"referenced":[6],"object":[7],"whose":[8],"non-spatial":[9],"attribute":[10],"values":[11,17],"are":[12],"significantly":[13],"different":[14],"from":[15],"the":[16,28,79],"of":[18,22,30,42,68],"its":[19],"neighborhood.":[20],"Identification":[21],"outliers":[24,56,117,123],"can":[25,92,110],"lead":[26],"to":[27,50,73],"discovery":[29],"unexpected,":[31],"interesting,":[32],"and":[33,88],"useful":[34],"patterns":[36],"for":[37],"further":[38],"analysis.":[39],"One":[40],"drawback":[41],"existing":[43,126],"methods":[44],"that":[46,107],"normal":[47],"objects":[48],"tend":[49],"be":[51],"falsely":[52],"detected":[53],"as":[54],"when":[57],"their":[58],"neighborhood":[59],"contains":[60],"true":[61,121],"outliers.":[63,96],"We":[64,77],"propose":[65],"suite":[67],"detection":[71,82],"algorithms":[72,90],"overcome":[74],"this":[75],"disadvantage.":[76],"formulate":[78],"problem":[83],"in":[84],"general":[86],"way":[87],"design":[89],"which":[91],"accurately":[93],"detect":[94],"In":[97],"addition,":[98],"using":[99],"real-world":[101],"census":[102],"data":[103],"set,":[104],"we":[105],"demonstrate":[106],"our":[108],"approaches":[109],"not":[111],"only":[112],"avoid":[113],"detecting":[114],"false":[115],"but":[118],"also":[119],"find":[120],"ignored":[124],"by":[125],"methods.":[127]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":12},{"year":2012,"cited_by_count":12}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}