{"id":"https://openalex.org/W2991328994","doi":"https://doi.org/10.1109/sdf.2019.8916633","title":"A Generic Anomaly Detection Approach Applied to Mixture-of-unigrams and Maritime Surveillance Data","display_name":"A Generic Anomaly Detection Approach Applied to Mixture-of-unigrams and Maritime Surveillance Data","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2991328994","doi":"https://doi.org/10.1109/sdf.2019.8916633","mag":"2991328994"},"language":"en","primary_location":{"id":"doi:10.1109/sdf.2019.8916633","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sdf.2019.8916633","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Sensor Data Fusion: Trends, Solutions, Applications (SDF)","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/A5100698859","display_name":"Yifan Zhou","orcid":"https://orcid.org/0000-0002-1477-5777"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Yifan Zhou","raw_affiliation_strings":["University of Liverpool,Department of Electrical Engineering and Electronics,Liverpool,UK","Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, UK"],"affiliations":[{"raw_affiliation_string":"University of Liverpool,Department of Electrical Engineering and Electronics,Liverpool,UK","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, UK","institution_ids":["https://openalex.org/I146655781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040355627","display_name":"James Wright","orcid":"https://orcid.org/0000-0002-5792-2116"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"James Wright","raw_affiliation_strings":["University of Liverpool,Department of Electrical Engineering and Electronics,Liverpool,UK","Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, UK"],"affiliations":[{"raw_affiliation_string":"University of Liverpool,Department of Electrical Engineering and Electronics,Liverpool,UK","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, UK","institution_ids":["https://openalex.org/I146655781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083636287","display_name":"Simon Maskell","orcid":"https://orcid.org/0000-0003-1917-2913"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Simon Maskell","raw_affiliation_strings":["University of Liverpool,Department of Electrical Engineering and Electronics,Liverpool,UK","Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, UK"],"affiliations":[{"raw_affiliation_string":"University of Liverpool,Department of Electrical Engineering and Electronics,Liverpool,UK","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, UK","institution_ids":["https://openalex.org/I146655781"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100698859"],"corresponding_institution_ids":["https://openalex.org/I146655781"],"apc_list":null,"apc_paid":null,"fwci":0.28,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.66940383,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9991999864578247,"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":0.9991999864578247,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.987500011920929,"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"}},{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9815999865531921,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.821743369102478},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7752447128295898},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7174285054206848},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6469879150390625},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6041100025177002},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5333243608474731},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.46166542172431946},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4262080192565918},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.42578452825546265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40206101536750793},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32194507122039795}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.821743369102478},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7752447128295898},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7174285054206848},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6469879150390625},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6041100025177002},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5333243608474731},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.46166542172431946},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4262080192565918},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.42578452825546265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40206101536750793},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32194507122039795},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sdf.2019.8916633","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sdf.2019.8916633","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Sensor Data Fusion: Trends, Solutions, Applications (SDF)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Life below water","id":"https://metadata.un.org/sdg/14"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1999499433","https://openalex.org/W2050576295","https://openalex.org/W2061922307","https://openalex.org/W2097089247","https://openalex.org/W2122646361","https://openalex.org/W2130494750","https://openalex.org/W2131904035","https://openalex.org/W2132870739","https://openalex.org/W2142669511","https://openalex.org/W2157573324","https://openalex.org/W2164489414","https://openalex.org/W2613480438","https://openalex.org/W2803941390","https://openalex.org/W4231510805","https://openalex.org/W4249610508","https://openalex.org/W6639619044","https://openalex.org/W6679329542","https://openalex.org/W6679539681","https://openalex.org/W6683398937"],"related_works":["https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2806741695","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160"],"abstract_inverted_index":{"This":[0,85],"paper":[1,86],"proposes":[2],"a":[3,18,50,55,88,119,133,158],"new":[4,89],"generic":[5],"method":[6,28,91],"to":[7,46,57,64,72,92,109,116,170],"detect":[8,47,93],"anomalies":[9,48,94],"(i.e.,":[10],"statistical":[11],"outliers)":[12],"which":[13,36,95],"can":[14],"be":[15],"used":[16,39],"with":[17,49],"generative":[19],"topic":[20,51],"model.":[21,103],"In":[22],"this":[23,27],"paper,":[24],"we":[25,130,156],"specify":[26],"in":[29,40],"the":[30,33,58,66,69,75,78,81,98,101,124,127,146],"context":[31],"of":[32,77,83,100,126,165,173],"Mixture-of-unigrams":[34],"model,":[35],"is":[37,44,62,107,168],"widely":[38],"text":[41],"mining.":[42],"It":[43],"possible":[45,169],"model":[52,159],"by":[53],"applying":[54],"threshold":[56,67],"likelihood.":[59],"However,":[60],"it":[61,167],"challenging":[63],"choose":[65],"since":[68],"choice":[70],"needs":[71],"consider":[73],"both":[74],"similarities":[76],"topics":[79],"and":[80],"length":[82],"documents.":[84],"describes":[87],"intuitive":[90,115],"simply":[96],"manipulates":[97],"output":[99],"trained":[102],"Such":[104],"an":[105],"approach":[106],"anticipated":[108],"have":[110],"parameters":[111],"that":[112],"are":[113],"more":[114],"define":[117],"for":[118,162],"given":[120],"problem.":[121],"To":[122],"assess":[123],"utility":[125],"proposed":[128],"approach,":[129],"also":[131],"present":[132],"use":[134],"case":[135],"involving":[136],"identifying":[137],"ships":[138,172],"misreporting":[139],"their":[140],"ship-type":[141],"using":[142,160],"geo-location":[143],"data":[144,161],"from":[145],"Automatic":[147],"Identification":[148],"System":[149],"(AIS)":[150],"messages.":[151],"We":[152],"show":[153],"that,":[154],"if":[155],"train":[157],"one":[163],"type":[164,175],"ship,":[166],"identify":[171],"another":[174],"as":[176],"anomalous.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2025-10-10T00:00:00"}
