{"id":"https://openalex.org/W3049725889","doi":"https://doi.org/10.1145/3399712","title":"Efficient Outlier Detection in Text Corpus Using Rare Frequency and Ranking","display_name":"Efficient Outlier Detection in Text Corpus Using Rare Frequency and Ranking","publication_year":2020,"publication_date":"2020-10-03","ids":{"openalex":"https://openalex.org/W3049725889","doi":"https://doi.org/10.1145/3399712","mag":"3049725889"},"language":"en","primary_location":{"id":"doi:10.1145/3399712","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3399712","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://eprints.qut.edu.au/200591/1/TKDD_R4_003_.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064640031","display_name":"Wathsala Anupama Mohotti","orcid":null},"institutions":[{"id":"https://openalex.org/I160993911","display_name":"Queensland University of Technology","ror":"https://ror.org/03pnv4752","country_code":"AU","type":"education","lineage":["https://openalex.org/I160993911"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Wathsala Anupama Mohotti","raw_affiliation_strings":["Queensland University of Technology, Australia"],"raw_orcid":"https://orcid.org/0000-0002-5720-7737","affiliations":[{"raw_affiliation_string":"Queensland University of Technology, Australia","institution_ids":["https://openalex.org/I160993911"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015158048","display_name":"Richi Nayak","orcid":"https://orcid.org/0000-0002-9954-0159"},"institutions":[{"id":"https://openalex.org/I160993911","display_name":"Queensland University of Technology","ror":"https://ror.org/03pnv4752","country_code":"AU","type":"education","lineage":["https://openalex.org/I160993911"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Richi Nayak","raw_affiliation_strings":["Queensland University of Technology, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Queensland University of Technology, Australia","institution_ids":["https://openalex.org/I160993911"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5064640031"],"corresponding_institution_ids":["https://openalex.org/I160993911"],"apc_list":null,"apc_paid":null,"fwci":1.4948,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.86463692,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"14","issue":"6","first_page":"1","last_page":"30"},"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9911999702453613,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9818999767303467,"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/outlier","display_name":"Outlier","score":0.7736956477165222},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.731200098991394},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6481691002845764},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.61567223072052},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6103060245513916},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4981815814971924},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4675651490688324},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45984163880348206},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4433170557022095},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41004830598831177},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3919869661331177},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3323633074760437},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.07995539903640747}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7736956477165222},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.731200098991394},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6481691002845764},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.61567223072052},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6103060245513916},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4981815814971924},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4675651490688324},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45984163880348206},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4433170557022095},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41004830598831177},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3919869661331177},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3323633074760437},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.07995539903640747},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3399712","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3399712","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},{"id":"pmh:oai:eprints.qut.edu.au:200591","is_oa":true,"landing_page_url":null,"pdf_url":"https://eprints.qut.edu.au/200591/1/TKDD_R4_003_.pdf","source":{"id":"https://openalex.org/S4306402607","display_name":"QUT ePrints (Queensland University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I160993911","host_organization_name":"Queensland University of Technology","host_organization_lineage":["https://openalex.org/I160993911"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"Contribution to Journal"}],"best_oa_location":{"id":"pmh:oai:eprints.qut.edu.au:200591","is_oa":true,"landing_page_url":null,"pdf_url":"https://eprints.qut.edu.au/200591/1/TKDD_R4_003_.pdf","source":{"id":"https://openalex.org/S4306402607","display_name":"QUT ePrints (Queensland University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I160993911","host_organization_name":"Queensland University of Technology","host_organization_lineage":["https://openalex.org/I160993911"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"Contribution to Journal"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W3049725889.pdf"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W57892430","https://openalex.org/W80463681","https://openalex.org/W80917968","https://openalex.org/W199035648","https://openalex.org/W560804666","https://openalex.org/W1489843519","https://openalex.org/W1516019649","https://openalex.org/W1673310716","https://openalex.org/W1858920103","https://openalex.org/W1960478704","https://openalex.org/W1974406477","https://openalex.org/W1974561058","https://openalex.org/W1978394996","https://openalex.org/W1981159181","https://openalex.org/W1982835105","https://openalex.org/W1984322889","https://openalex.org/W1986332411","https://openalex.org/W1988833430","https://openalex.org/W2019014808","https://openalex.org/W2041565863","https://openalex.org/W2049058890","https://openalex.org/W2061122559","https://openalex.org/W2076471773","https://openalex.org/W2077775960","https://openalex.org/W2086662461","https://openalex.org/W2089923519","https://openalex.org/W2108501461","https://openalex.org/W2123256336","https://openalex.org/W2126184790","https://openalex.org/W2126281141","https://openalex.org/W2129281431","https://openalex.org/W2144182447","https://openalex.org/W2153487386","https://openalex.org/W2157133710","https://openalex.org/W2160642098","https://openalex.org/W2197830862","https://openalex.org/W2200445523","https://openalex.org/W2250539671","https://openalex.org/W2338990760","https://openalex.org/W2622411536","https://openalex.org/W2731977498","https://openalex.org/W2741096554","https://openalex.org/W2785389416","https://openalex.org/W2807198477","https://openalex.org/W2808018025","https://openalex.org/W2892383154","https://openalex.org/W2905018049","https://openalex.org/W2906890643","https://openalex.org/W2915049075","https://openalex.org/W2937423263","https://openalex.org/W2949547296","https://openalex.org/W2963307331","https://openalex.org/W2963413667","https://openalex.org/W2963521413","https://openalex.org/W3005095525","https://openalex.org/W3010805239","https://openalex.org/W3105625590","https://openalex.org/W3123712780","https://openalex.org/W3130685565","https://openalex.org/W4230765542","https://openalex.org/W4247105055","https://openalex.org/W4253461361","https://openalex.org/W4254182148","https://openalex.org/W4256177618","https://openalex.org/W4298068628"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W4213170381","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W1598471830","https://openalex.org/W3107369729"],"abstract_inverted_index":{"Outlier":[0],"detection":[1,42,49,160],"in":[2,16,106,161],"text":[3,20,71],"data":[4,21,55],"collections":[5],"has":[6],"become":[7],"significant":[8],"due":[9],"to":[10,78,130,172],"the":[11,17,28,60,91,111,127,132,137,148,156,173],"need":[12,37],"of":[13,19,31,62,66,140,158],"finding":[14,95,136],"anomalies":[15],"myriad":[18],"sources.":[22],"High":[23],"feature":[24],"dimensionality,":[25],"together":[26],"with":[27,44,70,90],"larger":[29,64],"size":[30],"these":[32,80],"document":[33,93,118,162],"collections,":[34],"presents":[35],"a":[36,63],"for":[38,98],"developing":[39,83],"accurate":[40],"outlier":[41,48,159],"methods":[43,50],"high":[45,107],"efficiency.":[46],"Traditional":[47],"face":[51],"several":[52,122],"challenges":[53],"including":[54],"sparseness,":[56],"distance":[57],"concentration,":[58],"and":[59,101,151],"presence":[61],"number":[65,139],"sub-groups":[67],"when":[68],"dealing":[69],"data.":[72],"In":[73],"this":[74],"article,":[75],"we":[76,120],"propose":[77],"address":[79],"issues":[81],"by":[82],"novel":[84,123],"concepts":[85],"such":[86],"as":[87,164,166],"presenting":[88],"documents":[89],"rare":[92,117],"frequency,":[94,119],"ranking-based":[96],"neighborhood":[97],"similarity":[99],"computation,":[100],"identifying":[102],"sub-dense":[103],"local":[104],"neighborhoods":[105],"dimensions.":[108],"To":[109],"improve":[110,155],"proposed":[112,149],"primary":[113],"method":[114,150],"based":[115],"on":[116],"present":[121],"ensemble":[124,153],"approaches":[125],"using":[126],"ranking":[128],"concept":[129],"reduce":[131],"false":[133],"identifications":[134],"while":[135],"higher":[138],"true":[141],"outliers.":[142],"Extensive":[143],"empirical":[144],"analysis":[145],"shows":[146],"that":[147],"its":[152],"variations":[154],"quality":[157],"repositories":[163],"well":[165],"they":[167],"are":[168],"found":[169],"scalable":[170],"compared":[171],"relevant":[174],"benchmarking":[175],"methods.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}