{"id":"https://openalex.org/W2365906439","doi":"https://doi.org/10.1145/2939672.2939846","title":"MANTRA","display_name":"MANTRA","publication_year":2016,"publication_date":"2016-08-08","ids":{"openalex":"https://openalex.org/W2365906439","doi":"https://doi.org/10.1145/2939672.2939846","mag":"2365906439"},"language":"en","primary_location":{"id":"doi:10.1145/2939672.2939846","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2939672.2939846","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","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/A5086456732","display_name":"Prithu Banerjee","orcid":"https://orcid.org/0009-0002-1190-2109"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Prithu Banerjee","raw_affiliation_strings":["University of British Columbia, Vancouver, BC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of British Columbia, Vancouver, BC, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042094014","display_name":"Pranali Yawalkar","orcid":null},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"education","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pranali Yawalkar","raw_affiliation_strings":["IIT Madras, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054697900","display_name":"Sayan Ranu","orcid":"https://orcid.org/0000-0003-4147-9372"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"education","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sayan Ranu","raw_affiliation_strings":["IIT Madras, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1415","last_page":"1424"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9983999729156494,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9980999827384949,"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/trajectory","display_name":"Trajectory","score":0.8084858655929565},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7794533371925354},{"id":"https://openalex.org/keywords/mantra","display_name":"Mantra","score":0.6843470335006714},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6798941493034363},{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.6769930720329285},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4726925194263458},{"id":"https://openalex.org/keywords/intuition","display_name":"Intuition","score":0.42757341265678406},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4181893765926361},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4009227752685547},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23592901229858398},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.08839789032936096}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8084858655929565},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7794533371925354},{"id":"https://openalex.org/C2778171436","wikidata":"https://www.wikidata.org/wiki/Q131510","display_name":"Mantra","level":2,"score":0.6843470335006714},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6798941493034363},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.6769930720329285},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4726925194263458},{"id":"https://openalex.org/C132010649","wikidata":"https://www.wikidata.org/wiki/Q189222","display_name":"Intuition","level":2,"score":0.42757341265678406},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4181893765926361},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4009227752685547},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23592901229858398},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.08839789032936096},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2939672.2939846","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2939672.2939846","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","id":"https://metadata.un.org/sdg/14","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W151127230","https://openalex.org/W1465304330","https://openalex.org/W1538548313","https://openalex.org/W1567097384","https://openalex.org/W1626398438","https://openalex.org/W1979818736","https://openalex.org/W1991737608","https://openalex.org/W2024021677","https://openalex.org/W2031674781","https://openalex.org/W2046466133","https://openalex.org/W2083236658","https://openalex.org/W2084335476","https://openalex.org/W2097241863","https://openalex.org/W2098759488","https://openalex.org/W2110413449","https://openalex.org/W2118371392","https://openalex.org/W2136975357","https://openalex.org/W2147880780","https://openalex.org/W2158689233","https://openalex.org/W2751555667","https://openalex.org/W2752779325","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W1605789739","https://openalex.org/W3210201299","https://openalex.org/W2890871679","https://openalex.org/W2808216538","https://openalex.org/W4388334207","https://openalex.org/W3189463824","https://openalex.org/W2319117687","https://openalex.org/W4287165197","https://openalex.org/W4387951051","https://openalex.org/W2073917588"],"abstract_inverted_index":{"In":[0],"this":[1,61],"paper,":[2],"we":[3,64,145],"study":[4,71],"the":[5,22,38,49,72,86,107,111,148],"problem":[6],"of":[7,93,99,114,133],"mining":[8],"temporally":[9,29],"anomalous":[10,30,76,116],"sub-trajectory":[11,27,50,94],"patterns":[12,43],"from":[13,37],"an":[14],"input":[15],"trajectory":[16,141],"in":[17,81],"a":[18,26,66,90],"scalable":[19,55],"manner.":[20],"Given":[21],"prevailing":[23],"road":[24],"conditions,":[25],"is":[28,53,103],"if":[31],"its":[32],"travel":[33],"time":[34],"deviates":[35],"significantly":[36],"expected":[39],"time.":[40],"Mining":[41],"these":[42],"requires":[44],"us":[45],"to":[46,75,83,109,152],"delve":[47],"into":[48,89],"space,":[51],"which":[52],"not":[54],"for":[56],"real-time":[57],"analytics.":[58],"To":[59],"overcome":[60],"scalability":[62],"challenge,":[63],"design":[65],"technique":[67],"called":[68],"MANTRA.":[69],"We":[70],"properties":[73],"unique":[74],"sub-trajectories":[77,102],"and":[78,123,143],"utilize":[79],"them":[80],"MANTRA":[82,127],"iteratively":[84],"refine":[85],"search":[87],"space":[88],"disjoint":[91],"set":[92,113],"islands.":[95],"The":[96],"expensive":[97],"enumeration":[98],"all":[100],"possible":[101],"performed":[104],"only":[105],"on":[106,120],"islands":[108],"compute":[110],"answer":[112],"maximal":[115],"sub-trajectories.":[117],"Extensive":[118],"experiments":[119],"both":[121],"real":[122],"synthetic":[124],"datasets":[125],"establish":[126],"as":[128],"more":[129],"than":[130,136],"3":[131],"orders":[132],"magnitude":[134],"faster":[135],"baseline":[137],"techniques.":[138],"Moreover,":[139],"through":[140],"classification":[142],"segmentation,":[144],"demonstrate":[146],"that":[147],"proposed":[149],"model":[150],"conforms":[151],"human":[153],"intuition.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2016-06-24T00:00:00"}
