{"id":"https://openalex.org/W4242076599","doi":"https://doi.org/10.23919/fusion49465.2021.9626956","title":"Clustering of maritime trajectories with AIS features for context learning","display_name":"Clustering of maritime trajectories with AIS features for context learning","publication_year":2021,"publication_date":"2021-11-01","ids":{"openalex":"https://openalex.org/W4242076599","doi":"https://doi.org/10.23919/fusion49465.2021.9626956"},"language":"en","primary_location":{"id":"doi:10.23919/fusion49465.2021.9626956","doi":"https://doi.org/10.23919/fusion49465.2021.9626956","is_oa":false,"landing_page_url":"https://doi.org/10.23919/fusion49465.2021.9626956","pdf_url":null,"source":{"id":"https://openalex.org/S4363608153","display_name":"International Conference on Information Fusion (FUSION)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 24th International Conference on Information Fusion (FUSION)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5041175197","display_name":"David S\u00e1nchez Pedroche","orcid":"https://orcid.org/0000-0001-8912-5165","observed_orcids":["https://orcid.org/0000-0001-8912-5165"]},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"David Sanchez Pedroche","raw_affiliation_strings":["Group GIAA, University Carlos III of Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Group GIAA, University Carlos III of Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026429672","display_name":"Daniel Amigo","orcid":"https://orcid.org/0000-0001-7138-5508","observed_orcids":["https://orcid.org/0000-0001-7138-5508"]},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Daniel Amigo Herrero","raw_affiliation_strings":["Group GIAA, University Carlos III of Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Group GIAA, University Carlos III of Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100653268","display_name":"Jes\u00fas Garc\u00eda","orcid":"https://orcid.org/0000-0002-6657-0618","observed_orcids":["https://orcid.org/0000-0002-6657-0618"]},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jesus Garcia Herrero","raw_affiliation_strings":["Group GIAA, University Carlos III of Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Group GIAA, University Carlos III of Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059583924","display_name":"Jos\u00e9 Manuel Molina","orcid":"https://orcid.org/0000-0002-7484-7357","observed_orcids":["https://orcid.org/0000-0002-7484-7357"]},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jose Manuel Molina Lopez","raw_affiliation_strings":["Group GIAA, University Carlos III of Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Group GIAA, University Carlos III of Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I50357001"],"apc_list":null,"apc_paid":null,"fwci":0.8373,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.6941572,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.8374000191688538,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11106","display_name":"Data Management and Algorithms","score":0.8374000191688538,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11622","display_name":"Maritime Navigation and Safety","score":0.10300000011920929,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.03669999912381172,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/automatic-identification-system","display_name":"Automatic Identification System","score":0.8080000281333923},{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.6919999718666077},{"id":"https://openalex.org/keywords/trajectory-clustering","display_name":"trajectory clustering","score":0.9300000071525574},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"dynamic time warping","score":0.8460000157356262},{"id":"https://openalex.org/keywords/trajectory-similarity","display_name":"trajectory similarity","score":0.9100000262260437},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"anomaly detection","score":0.9549999833106995},{"id":"https://openalex.org/keywords/ship-data","display_name":"ship data","score":0.42399999499320984},{"id":"https://openalex.org/keywords/contextual-learning","display_name":"contextual learning","score":0.9079999923706055}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.791612982749939},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7777920961380005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7770946025848389},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6301978826522827},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6258319020271301},{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.5778895020484924},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5138800144195557},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5133846998214722},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4960351884365082},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.45217493176460266},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.44643956422805786},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4414430260658264},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4132983684539795},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32715797424316406},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.20588639378547668},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.20242854952812195},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16329997777938843},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/fusion49465.2021.9626956","doi":"https://doi.org/10.23919/fusion49465.2021.9626956","is_oa":false,"landing_page_url":"https://doi.org/10.23919/fusion49465.2021.9626956","pdf_url":null,"source":{"id":"https://openalex.org/S4363608153","display_name":"International Conference on Information Fusion (FUSION)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 24th International Conference on Information Fusion (FUSION)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320324211","display_name":"Ministry of Economy","ror":"https://ror.org/02fn8ac40"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W116902681","https://openalex.org/W1673310716","https://openalex.org/W1981398125","https://openalex.org/W1993220166","https://openalex.org/W1995462061","https://openalex.org/W2060346657","https://openalex.org/W2069401302","https://openalex.org/W2075236191","https://openalex.org/W2103632679","https://openalex.org/W2105934661","https://openalex.org/W2117397690","https://openalex.org/W2144994235","https://openalex.org/W2148143831","https://openalex.org/W2165315096","https://openalex.org/W2167225252","https://openalex.org/W2169572027","https://openalex.org/W2338318698","https://openalex.org/W2749776958","https://openalex.org/W2753820606","https://openalex.org/W2772832743","https://openalex.org/W2889062794","https://openalex.org/W2905283274","https://openalex.org/W2912934741","https://openalex.org/W2969677566","https://openalex.org/W2987583674","https://openalex.org/W3003331180","https://openalex.org/W3011190199","https://openalex.org/W3018019331","https://openalex.org/W3030514217","https://openalex.org/W3040019743","https://openalex.org/W3184022454","https://openalex.org/W4243367342"],"related_works":["https://openalex.org/W4387653815","https://openalex.org/W4307950634","https://openalex.org/W4211236260","https://openalex.org/W3193812513","https://openalex.org/W4304208796","https://openalex.org/W2899187527","https://openalex.org/W4391811521","https://openalex.org/W4387247600","https://openalex.org/W4402725358","https://openalex.org/W2744006307"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"an":[3,26,78],"analysis":[4],"on":[5,33],"Automatic":[6],"Identification":[7],"System":[8],"(AIS)":[9],"real":[10],"world":[11],"ship":[12],"data":[13,134],"to":[14,21,40,67,110,114,132],"build":[15],"a":[16,37,45,69,88,94],"system":[17],"with":[18],"the":[19,34,57,60,75,91,115,119,124],"capability":[20],"extract":[22],"useful":[23],"information":[24],"for":[25],"anomaly":[27],"detection":[28],"problem.":[29],"The":[30,98],"study":[31,125],"focuses":[32],"adjustment":[35],"of":[36,53,80,82,90,118,129],"clustering":[38],"technique":[39],"trajectory":[41,62,86,92],"data,":[42],"specifically":[43],"using":[44],"DBSCAN":[46],"algorithm":[47],"that":[48,101],"is":[49,65],"adapted":[50],"by":[51],"means":[52],"two":[54,72],"approaches.":[55],"On":[56,74],"one":[58],"hand,":[59,77],"DTW":[61],"similarity":[63],"metric":[64],"used":[66,120],"obtain":[68],"distance":[70],"between":[71],"trajectories.":[73],"other":[76],"extraction":[79],"features":[81],"interest":[83],"from":[84],"each":[85],"allowing":[87],"summary":[89],"in":[93],"single":[95],"multidimensional":[96],"instance.":[97],"results":[99],"show":[100],"both":[102],"approaches":[103,131],"are":[104],"feasible,":[105],"although":[106],"not":[107],"very":[108],"scalable":[109],"larger":[111],"problems":[112],"due":[113],"computational":[116],"complexity":[117],"algorithms.":[121],"In":[122],"addition,":[123],"analyses":[126],"possible":[127],"uses":[128],"these":[130],"existing":[133],"mining":[135],"problems.":[136]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2022-05-12T00:00:00"}