{"id":"https://openalex.org/W2998070851","doi":"https://doi.org/10.1007/978-3-030-38081-6_2","title":"Uncovering Hidden Concepts from AIS Data: A Network Abstraction of Maritime Traffic for Anomaly Detection","display_name":"Uncovering Hidden Concepts from AIS Data: A Network Abstraction of Maritime Traffic for Anomaly Detection","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W2998070851","doi":"https://doi.org/10.1007/978-3-030-38081-6_2","mag":"2998070851"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-030-38081-6_2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-030-38081-6_2","pdf_url":"https://link.springer.com/content/pdf/10.1007%2F978-3-030-38081-6_2.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007%2F978-3-030-38081-6_2.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060088887","display_name":"Ioannis Kontopoulos","orcid":"https://orcid.org/0000-0001-9862-8944"},"institutions":[{"id":"https://openalex.org/I32762134","display_name":"Harokopio University of Athens","ror":"https://ror.org/02k5gp281","country_code":"GR","type":"education","lineage":["https://openalex.org/I32762134"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Ioannis Kontopoulos","raw_affiliation_strings":["Department of Informatics and Telematics, Harokopio University of Athens, Athens, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Informatics and Telematics, Harokopio University of Athens, Athens, Greece","institution_ids":["https://openalex.org/I32762134"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056484904","display_name":"Iraklis Varlamis","orcid":"https://orcid.org/0000-0002-0876-8167"},"institutions":[{"id":"https://openalex.org/I32762134","display_name":"Harokopio University of Athens","ror":"https://ror.org/02k5gp281","country_code":"GR","type":"education","lineage":["https://openalex.org/I32762134"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Iraklis Varlamis","raw_affiliation_strings":["Department of Informatics and Telematics, Harokopio University of Athens, Athens, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Informatics and Telematics, Harokopio University of Athens, Athens, Greece","institution_ids":["https://openalex.org/I32762134"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021420035","display_name":"Konstantinos Tserpes","orcid":"https://orcid.org/0000-0001-5183-1443"},"institutions":[{"id":"https://openalex.org/I32762134","display_name":"Harokopio University of Athens","ror":"https://ror.org/02k5gp281","country_code":"GR","type":"education","lineage":["https://openalex.org/I32762134"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Konstantinos Tserpes","raw_affiliation_strings":["Department of Informatics and Telematics, Harokopio University of Athens, Athens, Greece","Harokopio University, Athens, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Informatics and Telematics, Harokopio University of Athens, Athens, Greece","institution_ids":["https://openalex.org/I32762134"]},{"raw_affiliation_string":"Harokopio University, Athens, Greece","institution_ids":["https://openalex.org/I32762134"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5060088887"],"corresponding_institution_ids":["https://openalex.org/I32762134"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":null,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11622","display_name":"Maritime Navigation and Safety","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11622","display_name":"Maritime Navigation and Safety","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9632999897003174,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8011954426765442},{"id":"https://openalex.org/keywords/traverse","display_name":"Traverse","score":0.7400356531143188},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.7014946341514587},{"id":"https://openalex.org/keywords/automatic-identification-system","display_name":"Automatic Identification System","score":0.6673312783241272},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.545526385307312},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.526557445526123},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5252796411514282},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46876972913742065},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.467360258102417},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4567199945449829},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.420743465423584},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29239559173583984},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10181230306625366},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.10102301836013794}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8011954426765442},{"id":"https://openalex.org/C176809094","wikidata":"https://www.wikidata.org/wiki/Q15401496","display_name":"Traverse","level":2,"score":0.7400356531143188},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.7014946341514587},{"id":"https://openalex.org/C146997752","wikidata":"https://www.wikidata.org/wiki/Q787197","display_name":"Automatic Identification System","level":2,"score":0.6673312783241272},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.545526385307312},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.526557445526123},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5252796411514282},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46876972913742065},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.467360258102417},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4567199945449829},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.420743465423584},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29239559173583984},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10181230306625366},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.10102301836013794},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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":2,"locations":[{"id":"doi:10.1007/978-3-030-38081-6_2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-030-38081-6_2","pdf_url":"https://link.springer.com/content/pdf/10.1007%2F978-3-030-38081-6_2.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},{"id":"pmh:oai:zenodo.org:3678139","is_oa":true,"landing_page_url":"https://zenodo.org/communities/master-h2020-msca-rise-project","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferencePaper"}],"best_oa_location":{"id":"doi:10.1007/978-3-030-38081-6_2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-030-38081-6_2","pdf_url":"https://link.springer.com/content/pdf/10.1007%2F978-3-030-38081-6_2.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"sustainable_development_goals":[{"score":0.550000011920929,"id":"https://metadata.un.org/sdg/14","display_name":"Life below water"}],"awards":[{"id":"https://openalex.org/G1494532855","display_name":"A data analytics, decision support and circular economy \u2013 based multi-layer optimisation platform towards a holistic energy efficiency, fuel consumption and emissions management of vessels","funder_award_id":"823916","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G483297964","display_name":"Multiple ASpects TrajEctoRy management and analysis","funder_award_id":"777695","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2998070851.pdf","grobid_xml":"https://content.openalex.org/works/W2998070851.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1576883264","https://openalex.org/W1587876863","https://openalex.org/W1673310716","https://openalex.org/W1864335429","https://openalex.org/W1981398125","https://openalex.org/W1981934656","https://openalex.org/W1995462061","https://openalex.org/W2083442964","https://openalex.org/W2100106957","https://openalex.org/W2164223054","https://openalex.org/W2265620001","https://openalex.org/W2620438329","https://openalex.org/W2743711613","https://openalex.org/W2788857645","https://openalex.org/W2790115023","https://openalex.org/W2799169867","https://openalex.org/W2879698168","https://openalex.org/W2898552906","https://openalex.org/W2899024236","https://openalex.org/W2934016713","https://openalex.org/W2934654247","https://openalex.org/W3103750832","https://openalex.org/W3123010800"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4245432329","https://openalex.org/W4300558037","https://openalex.org/W4377864969"],"abstract_inverted_index":{"The":[0,127,180,214,240],"compulsory":[1],"use":[2],"of":[3,31,51,69,82,97,134,162,177],"Automatic":[4],"Identification":[5],"System":[6],"(AIS)":[7],"for":[8,23,66,103,196,277],"many":[9],"vessel":[10,71,203],"types,":[11],"which":[12,170],"has":[13,19],"been":[14],"enforced":[15],"by":[16,121],"naval":[17,95],"regulations,":[18],"opened":[20],"new":[21],"opportunities":[22],"maritime":[24,83],"surveillance.":[25],"AIS":[26,52,207],"transponders":[27],"are":[28],"rich":[29],"sources":[30],"information":[32,44,143],"that":[33,85,92,115,148,217,235],"everyone":[34],"can":[35,54,244],"collect":[36],"using":[37,224],"an":[38,78,153,160,256],"RF":[39],"receiver":[40],"and":[41,62,111,138,193,247,281],"provide":[42],"real-time":[43,60],"about":[45,144],"vessels\u2019":[46,265],"position.":[47],"Properly":[48],"taking":[49],"advantage":[50],"data,":[53],"uncover":[55],"potential":[56,276],"illegal":[57],"behavior,":[58],"offer":[59],"alerts":[61],"notify":[63],"the":[64,118,132,145,163,172,178,186,198,211,226,274],"authorities":[65],"any":[67],"kind":[68],"anomalous":[70],"behavior.":[72],"In":[73],"this":[74,135,218],"article,":[75],"we":[76],"extend":[77],"existing":[79],"network":[80,136,242],"abstraction":[81,137],"traffic,":[84],"is":[86],"based":[87,166],"on":[88,131,269,284],"nodes":[89],"(called":[90,113],"way-points)":[91],"correspond":[93,116],"to":[94,117,261],"areas":[96],"long":[98],"stays":[99],"or":[100],"major":[101],"turns":[102],"vessels":[104,122,149],"(e.g.":[105],"ports,":[106],"capes,":[107],"offshore":[108],"platforms":[109],"etc.)":[110],"edges":[112],"traversals)":[114],"routes":[119],"followed":[120],"between":[123,200],"two":[124,201],"consecutive":[125,202,206],"way-points.":[126],"current":[128],"work,":[129],"focuses":[130],"connections":[133],"enriches":[139],"them":[140],"with":[141,250],"semantic":[142],"different":[146],"ways":[147],"employ":[150],"when":[151],"traversing":[152],"edge.":[154],"For":[155],"achieving":[156],"this,":[157],"it":[158],"proposes":[159],"alternative":[161,182],"popular":[164],"density":[165],"clustering":[167],"algorithm":[168],"DB-Scan,":[169],"modifies":[171],"proximity":[173],"parameter":[174],"(i.e.":[175],"epsilon)":[176],"algorithm.":[179],"proposed":[181],"employs":[183],"in":[184,188,233,255,259,264],"tandem":[185],"difference":[187],"(i)":[189],"speed,":[190],"(ii)":[191],"course":[192],"(iii)":[194],"position":[195],"defining":[197],"distance":[199,228],"positions":[204],"(two":[205],"signals":[208],"received":[209],"from":[210],"same":[212],"vessel).":[213],"results":[215,232,268],"show":[216,273],"combination":[219],"performs":[220],"significantly":[221],"better":[222],"than":[223],"only":[225],"spatial":[227],"and,":[229],"more":[230],"importantly,":[231],"clusters":[234],"have":[236],"very":[237],"interesting":[238],"properties.":[239],"enriched":[241],"model":[243],"be":[245],"processed":[246],"further":[248],"examined":[249],"data":[251],"mining":[252],"techniques,":[253],"even":[254],"unsupervised":[257],"manner,":[258],"order":[260],"identify":[262],"anomalies":[263],"trajectories.":[266],"Experimental":[267],"a":[270,285],"real":[271],"dataset":[272],"network\u2019s":[275],"detecting":[278],"trajectory":[279],"outliers":[280],"uncovering":[282],"deviations":[283],"vessel\u2019s":[286],"route.":[287]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-20T07:56:41.581041","created_date":"2025-10-10T00:00:00"}
