{"id":"https://openalex.org/W2810513759","doi":"https://doi.org/10.1109/fskd.2017.8393299","title":"Structural outlier detection: A tourist walk approach","display_name":"Structural outlier detection: A tourist walk approach","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2810513759","doi":"https://doi.org/10.1109/fskd.2017.8393299","mag":"2810513759"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2017.8393299","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2017.8393299","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","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/A5021310317","display_name":"Rafael Delalibera Rodrigues","orcid":"https://orcid.org/0000-0001-7433-1951"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Rafael D. Rodrigues","raw_affiliation_strings":["Faculty of Philosophy, University of S\u00e3o Paulo (USP), Ribeir\u00e3o Preto, SP, Brazil"],"affiliations":[{"raw_affiliation_string":"Faculty of Philosophy, University of S\u00e3o Paulo (USP), Ribeir\u00e3o Preto, SP, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100697945","display_name":"Liang Zhao","orcid":"https://orcid.org/0000-0002-1502-6604"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Liang Zhao","raw_affiliation_strings":["Faculty of Philosophy, University of S\u00e3o Paulo (USP), Ribeir\u00e3o Preto, SP, Brazil"],"affiliations":[{"raw_affiliation_string":"Faculty of Philosophy, University of S\u00e3o Paulo (USP), Ribeir\u00e3o Preto, SP, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101062773","display_name":"Qiusheng Zheng","orcid":"https://orcid.org/0000-0002-9067-1806"},"institutions":[{"id":"https://openalex.org/I132586189","display_name":"Zhongyuan University of Technology","ror":"https://ror.org/0360zcg91","country_code":"CN","type":"education","lineage":["https://openalex.org/I132586189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiusheng Zheng","raw_affiliation_strings":["School of Computer Science, Zhongyuan University of Technology, ZhengZhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Zhongyuan University of Technology, ZhengZhou, China","institution_ids":["https://openalex.org/I132586189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021026205","display_name":"Junbao Zhang","orcid":"https://orcid.org/0000-0003-1335-752X"},"institutions":[{"id":"https://openalex.org/I132586189","display_name":"Zhongyuan University of Technology","ror":"https://ror.org/0360zcg91","country_code":"CN","type":"education","lineage":["https://openalex.org/I132586189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junbao Zhang","raw_affiliation_strings":["Zhongyuan University of Technology, Zhengzhou, Henan, CN"],"affiliations":[{"raw_affiliation_string":"Zhongyuan University of Technology, Zhengzhou, Henan, CN","institution_ids":["https://openalex.org/I132586189"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5021310317"],"corresponding_institution_ids":["https://openalex.org/I17974374"],"apc_list":null,"apc_paid":null,"fwci":0.195,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.65981137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"382","last_page":"387"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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":1.0,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9803000092506409,"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/T12391","display_name":"Artificial Immune Systems Applications","score":0.9670000076293945,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.8568694591522217},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7672717571258545},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6969798803329468},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6001112461090088},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5417831540107727},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5250622630119324},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.49142444133758545},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.47354525327682495},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4647146463394165},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4248204529285431},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.4170757830142975},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15433844923973083}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.8568694591522217},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7672717571258545},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6969798803329468},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6001112461090088},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5417831540107727},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5250622630119324},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.49142444133758545},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.47354525327682495},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4647146463394165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4248204529285431},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.4170757830142975},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15433844923973083},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2017.8393299","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2017.8393299","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W39464122","https://openalex.org/W2026413914","https://openalex.org/W2045761097","https://openalex.org/W2048869825","https://openalex.org/W2049058890","https://openalex.org/W2062980342","https://openalex.org/W2122646361","https://openalex.org/W2137130182","https://openalex.org/W2144182447","https://openalex.org/W2170314592","https://openalex.org/W2324488761","https://openalex.org/W2342529049","https://openalex.org/W2343025113","https://openalex.org/W2397800115","https://openalex.org/W2500517591","https://openalex.org/W2963090454","https://openalex.org/W4238769381","https://openalex.org/W4245050711","https://openalex.org/W4254182148"],"related_works":["https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W1598471830","https://openalex.org/W3107369729","https://openalex.org/W4390662392","https://openalex.org/W71955863","https://openalex.org/W2359185137","https://openalex.org/W2610918223"],"abstract_inverted_index":{"Outlier":[0],"detection":[1,32],"is":[2,14,179,187],"a":[3,29,48,52,67,74,180],"fundamental":[4],"task":[5],"for":[6],"knowledge":[7],"discovery":[8],"in":[9,59,73,189],"data":[10,17,40,49,85,119,153,173],"mining.":[11],"Its":[12],"aim":[13],"to":[15,96,191],"detect":[16,136],"patterns":[18],"that":[19],"deviate":[20],"from":[21,38],"normal":[22,152],"behavior.":[23],"In":[24,94],"this":[25],"paper,":[26],"we":[27],"present":[28],"new":[30],"outlier":[31,54],"technique":[33],"using":[34],"tourist":[35,61,162],"walks":[36,163],"starting":[37],"each":[39],"sample":[41,50],"and":[42,83,168],"varying":[43,157],"the":[44,91,99,103,114,117,158,161,172],"memory":[45,159],"size.":[46],"Specifically,":[47],"gets":[51,66],"higher":[53],"score":[55,69],"if":[56,70],"it":[57,65,71],"participates":[58,72],"few":[60],"walk":[62],"attractors,":[63],"while":[64],"low":[68],"large":[75],"number":[76],"of":[77,90,116,122,171],"attractors.":[78],"Experimental":[79],"results":[80],"on":[81],"artificial":[82],"real":[84],"sets":[86],"show":[87],"good":[88],"performance":[89],"proposed":[92,100,177],"method.":[93],"comparison":[95],"classical":[97,142],"methods,":[98],"one":[101,185],"shows":[102],"following":[104],"salient":[105],"features:":[106],"1)":[107],"It":[108,134],"finds":[109],"out":[110],"outliers":[111,140,148],"by":[112],"identifying":[113],"structure":[115],"input":[118],"set":[120],"instead":[121],"considering":[123],"only":[124,138,184],"physical":[125],"features,":[126],"such":[127],"as":[128,141],"distance,":[129],"similarity":[130],"or":[131],"density.":[132],"2)":[133],"can":[135,164],"not":[137],"external":[139],"methods":[143],"do,":[144],"but":[145],"also":[146],"internal":[147],"staying":[149],"among":[150],"various":[151],"groups.":[154],"3)":[155],"By":[156],"size,":[160],"characterize":[165],"both":[166],"local":[167],"global":[169],"structures":[170],"set.":[174],"4)":[175],"The":[176],"method":[178],"deterministic":[181],"technique.":[182],"Therefore,":[183],"run":[186],"sufficient,":[188],"contrast":[190],"stochastic":[192],"techniques,":[193],"which":[194],"require":[195],"many":[196],"runs.":[197]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
