{"id":"https://openalex.org/W4404105988","doi":"https://doi.org/10.1145/3681765.3698465","title":"Context-aware Trajectory Anomaly Detection","display_name":"Context-aware Trajectory Anomaly Detection","publication_year":2024,"publication_date":"2024-10-29","ids":{"openalex":"https://openalex.org/W4404105988","doi":"https://doi.org/10.1145/3681765.3698465"},"language":"en","primary_location":{"id":"doi:10.1145/3681765.3698465","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3681765.3698465","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3681765.3698465","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Geospatial Anomaly Detection","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3681765.3698465","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102816759","display_name":"Haoji Hu","orcid":"https://orcid.org/0000-0002-6548-2421"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Haoji Hu","raw_affiliation_strings":["Department of Computer Science & Engineering, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100646674","display_name":"Jina Kim","orcid":"https://orcid.org/0000-0003-1140-6113"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jina Kim","raw_affiliation_strings":["Department of Computer Science & Engineering, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102289960","display_name":"James Zhou","orcid":"https://orcid.org/0000-0001-6498-9274"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinwei Zhou","raw_affiliation_strings":["Department of Computer Science & Engineering, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114540688","display_name":"Sofia Kirsanova","orcid":"https://orcid.org/0009-0007-7402-2615"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sofia Kirsanova","raw_affiliation_strings":["Department of Computer Science & Engineering, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078858243","display_name":"JangHyeon Lee","orcid":"https://orcid.org/0000-0003-4447-3697"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Janghyeon Lee","raw_affiliation_strings":["Department of Computer Science & Engineering, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045786247","display_name":"Yao\u2010Yi Chiang","orcid":"https://orcid.org/0000-0002-8923-0130"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"YaoYi Chiang","raw_affiliation_strings":["Department of Computer Science & Engineering, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5102816759"],"corresponding_institution_ids":["https://openalex.org/I130238516"],"apc_list":null,"apc_paid":null,"fwci":1.8131,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.87789446,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"12","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/trajectory","display_name":"Trajectory","score":0.7659679651260376},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7059705257415771},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6695363521575928},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6546478867530823},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4128870666027069},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26403892040252686},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.11715620756149292},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06371891498565674}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7659679651260376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7059705257415771},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6695363521575928},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6546478867530823},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4128870666027069},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26403892040252686},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11715620756149292},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06371891498565674},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3681765.3698465","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3681765.3698465","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3681765.3698465","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Geospatial Anomaly Detection","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3681765.3698465","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3681765.3698465","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3681765.3698465","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Geospatial Anomaly Detection","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1894767750","display_name":null,"funder_award_id":"140D0423C0033","funder_id":"https://openalex.org/F4320333051","funder_display_name":"Intelligence Advanced Research Projects Activity"}],"funders":[{"id":"https://openalex.org/F4320333051","display_name":"Intelligence Advanced Research Projects Activity","ror":"https://ror.org/01v3fsc55"},{"id":"https://openalex.org/F4320333452","display_name":"Interior Business Center","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4404105988.pdf","grobid_xml":"https://content.openalex.org/works/W4404105988.grobid-xml"},"referenced_works_count":7,"referenced_works":["https://openalex.org/W2101156862","https://openalex.org/W2605350416","https://openalex.org/W3005893373","https://openalex.org/W3006775836","https://openalex.org/W3041589212","https://openalex.org/W4287868670","https://openalex.org/W4318718563"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W3132773133","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969"],"abstract_inverted_index":{"Trajectory":[0],"anomaly":[1,18,82,125,158],"detection":[2,19,83],"is":[3,95],"crucial":[4],"for":[5,155],"effective":[6],"decision-making":[7],"in":[8,130],"urban":[9],"and":[10,28,110,133],"human":[11],"mobility":[12],"management.":[13],"Existing":[14],"methods":[15,142],"of":[16,32,61,116,124],"trajectory":[17,25,99,157],"generally":[20],"focus":[21],"on":[22,45,69,97],"training":[23],"a":[24,34,80,98,152],"generative":[26],"model":[27],"evaluating":[29],"the":[30,46,50,122,136],"likelihood":[31],"reconstructing":[33],"given":[35],"trajectory.":[36],"However,":[37],"previous":[38],"work":[39],"often":[40],"lacks":[41],"important":[42],"contextual":[43,87,104,111,117,146],"information":[44,52,58,68,88,118],"trajectory,":[47],"such":[48,106],"as":[49,107],"agent's":[51],"(e.g.,":[53,59],"agent":[54,108],"ID)":[55],"or":[56],"geographic":[57],"Points":[60],"Interest":[62],"(POI)),":[63],"which":[64],"could":[65],"provide":[66],"additional":[67],"accurately":[70],"capturing":[71],"anomalous":[72],"behaviors.":[73],"To":[74],"fill":[75],"this":[76,149],"gap,":[77],"we":[78],"propose":[79],"context-aware":[81],"approach":[84,138],"that":[85,135],"models":[86],"related":[89],"to":[90,120],"trajectories.":[91],"The":[92,114],"proposed":[93,137],"method":[94],"based":[96],"reconstruction":[100],"framework":[101],"guided":[102],"by":[103,143],"factors":[105],"ID":[109],"POI":[112],"embedding.":[113],"injection":[115],"aims":[119],"improve":[121],"performance":[123],"detection.":[126,159],"We":[127],"conducted":[128],"experiments":[129],"two":[131],"cities":[132],"demonstrated":[134],"significantly":[139],"outperformed":[140],"existing":[141],"effectively":[144],"modeling":[145],"information.":[147],"Overall,":[148],"paper":[150],"paves":[151],"new":[153],"direction":[154],"advancing":[156]},"counts_by_year":[{"year":2025,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}