{"id":"https://openalex.org/W3107295851","doi":"https://doi.org/10.1142/s0219649220500409","title":"A Novel Approach for Mining Time and Space Proximity-based Frequent Sequential Patterns from Trajectory Data","display_name":"A Novel Approach for Mining Time and Space Proximity-based Frequent Sequential Patterns from Trajectory Data","publication_year":2020,"publication_date":"2020-11-28","ids":{"openalex":"https://openalex.org/W3107295851","doi":"https://doi.org/10.1142/s0219649220500409","mag":"3107295851"},"language":"en","primary_location":{"id":"doi:10.1142/s0219649220500409","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219649220500409","pdf_url":null,"source":{"id":"https://openalex.org/S30163770","display_name":"Journal of Information & Knowledge Management","issn_l":"0219-6492","issn":["0219-6492","1793-6926"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Information & Knowledge Management","raw_type":"journal-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/A5029841282","display_name":"R. Praneetha Sree","orcid":"https://orcid.org/0000-0002-0374-8191"},"institutions":[{"id":"https://openalex.org/I121750182","display_name":"National Institute of Technology Warangal","ror":"https://ror.org/017ebfz38","country_code":"IN","type":"education","lineage":["https://openalex.org/I121750182"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rayanoothala Praneetha Sree","raw_affiliation_strings":["Department of Computer Science & Engineering, National Institute of Technology Warangal, Warangal 506004, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, National Institute of Technology Warangal, Warangal 506004, India","institution_ids":["https://openalex.org/I121750182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111965646","display_name":"D. V. L. N. Somayajulu","orcid":null},"institutions":[{"id":"https://openalex.org/I121750182","display_name":"National Institute of Technology Warangal","ror":"https://ror.org/017ebfz38","country_code":"IN","type":"education","lineage":["https://openalex.org/I121750182"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"D. V. L. N. Somayajulu","raw_affiliation_strings":["Department of Computer Science & Engineering, National Institute of Technology Warangal, Warangal 506004, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, National Institute of Technology Warangal, Warangal 506004, India","institution_ids":["https://openalex.org/I121750182"]}]},{"author_position":"last","author":{"id":null,"display_name":"S. Ravichandra","orcid":null},"institutions":[{"id":"https://openalex.org/I121750182","display_name":"National Institute of Technology Warangal","ror":"https://ror.org/017ebfz38","country_code":"IN","type":"education","lineage":["https://openalex.org/I121750182"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"S. Ravichandra","raw_affiliation_strings":["Department of Computer Science & Engineering, National Institute of Technology Warangal, Warangal 506004, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, National Institute of Technology Warangal, Warangal 506004, India","institution_ids":["https://openalex.org/I121750182"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1521,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46138795,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"19","issue":"04","first_page":"2050040","last_page":"2050040"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998999834060669,"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/T11106","display_name":"Data Management and Algorithms","score":0.9998999834060669,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9976000189781189,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9902999997138977,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.8065444827079773},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7149367332458496},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.689262866973877},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6107865571975708},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5819904208183289},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.49161702394485474},{"id":"https://openalex.org/keywords/euclidean-space","display_name":"Euclidean space","score":0.47797080874443054},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46755683422088623},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4510188102722168},{"id":"https://openalex.org/keywords/metric-space","display_name":"Metric space","score":0.4406135678291321},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43723300099372864},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4366835057735443},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34309089183807373},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2314755916595459}],"concepts":[{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.8065444827079773},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7149367332458496},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.689262866973877},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6107865571975708},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5819904208183289},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.49161702394485474},{"id":"https://openalex.org/C186450821","wikidata":"https://www.wikidata.org/wiki/Q17295","display_name":"Euclidean space","level":2,"score":0.47797080874443054},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46755683422088623},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4510188102722168},{"id":"https://openalex.org/C198043062","wikidata":"https://www.wikidata.org/wiki/Q180953","display_name":"Metric space","level":2,"score":0.4406135678291321},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43723300099372864},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4366835057735443},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34309089183807373},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2314755916595459},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1142/s0219649220500409","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219649220500409","pdf_url":null,"source":{"id":"https://openalex.org/S30163770","display_name":"Journal of Information & Knowledge Management","issn_l":"0219-6492","issn":["0219-6492","1793-6926"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Information & Knowledge Management","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:wsi:jikmxx:v:19:y:2020:i:04:n:s0219649220500409","is_oa":false,"landing_page_url":"http://www.worldscientific.com/doi/abs/10.1142/S0219649220500409","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1551268746","https://openalex.org/W1837913551","https://openalex.org/W1841789789","https://openalex.org/W2008386386","https://openalex.org/W2012580531","https://openalex.org/W2034852725","https://openalex.org/W2054662802","https://openalex.org/W2072957930","https://openalex.org/W2073252985","https://openalex.org/W2077451659","https://openalex.org/W2111830885","https://openalex.org/W2118371392","https://openalex.org/W2126194848","https://openalex.org/W2141136363","https://openalex.org/W2147880780","https://openalex.org/W2165169065","https://openalex.org/W2169164179","https://openalex.org/W2186751573","https://openalex.org/W2203070563","https://openalex.org/W2217442075","https://openalex.org/W2397826031","https://openalex.org/W2561675875","https://openalex.org/W2807054217","https://openalex.org/W2909968474","https://openalex.org/W2950051816","https://openalex.org/W4250331344","https://openalex.org/W4300384932","https://openalex.org/W4302789841","https://openalex.org/W4312390606","https://openalex.org/W4385400191"],"related_works":["https://openalex.org/W2169159254","https://openalex.org/W1992732116","https://openalex.org/W2067578116","https://openalex.org/W3174657038","https://openalex.org/W2902494752","https://openalex.org/W2592471899","https://openalex.org/W2382061536","https://openalex.org/W4390673421","https://openalex.org/W4310043907","https://openalex.org/W2912862582"],"abstract_inverted_index":{"Trajectory":[0],"Data":[1],"have":[2,110],"been":[3],"considered":[4],"as":[5,188],"a":[6,80],"treasure":[7],"for":[8,35,44],"various":[9,185],"hidden":[10],"patterns":[11],"which":[12,77],"provide":[13],"deeper":[14],"understanding":[15],"of":[16,82,129,135,141,145,190,198,223,228],"the":[17,63,66,98,112,121,127,132,136,139,168,184,229,235],"underlying":[18],"moving":[19,230],"objects.":[20,137],"Several":[21],"studies":[22],"are":[23,40,148,164,181,207,218],"focused":[24],"to":[25,52,61,96,115,125,166,220,225,233],"extract":[26],"repetitive,":[27],"frequent":[28,146],"and":[29,57,150,179,203,232],"group":[30],"patterns.":[31],"Conventional":[32],"algorithms":[33],"defined":[34],"Sequential":[36,160,216],"Patterns":[37,217],"Mining":[38],"problems":[39],"not":[41],"directly":[42],"applicable":[43],"trajectory":[45,202],"data.":[46,67],"Space":[47],"Partitioning":[48],"strategies":[49],"were":[50],"proposed":[51,95],"capture":[53],"space":[54,103],"proximity":[55,60,72,104],"first":[56,73],"then":[58,151],"time":[59,71,86],"discover":[62],"knowledge":[64,118,224],"in":[65,88,152,200,237],"Our":[68,100],"proposal":[69],"addresses":[70],"by":[74],"identifying":[75],"trajectories":[76,130,147],"meet":[78],"at":[79],"minimum":[81],"[Formula:":[83,156,193],"see":[84,157,194],"text]":[85,158,195],"stamps":[87],"sequence.":[89],"A":[90],"novel":[91],"tree":[92],"structure":[93],"is":[94,177],"ease":[97],"process.":[99],"method":[101],"investigates":[102],"using":[105],"Mahalanobis":[106],"distance":[107,114,173],"(MD).":[108],"We":[109],"used":[111],"Manhattan":[113],"form":[116,155],"prior":[117],"that":[119],"helps":[120],"supervised":[122],"learning-based":[123],"MD":[124,169],"derive":[126],"clusters":[128,144],"along":[131],"true":[133],"spreads":[134],"With":[138],"help":[140],"minsup":[142],"threshold,":[143],"found":[149],"sequence":[153],"they":[154],"length":[159],"Patterns.":[161],"Illustrative":[162],"examples":[163],"provided":[165],"compare":[167],"metric":[170],"with":[171],"Euclidean":[172],"metric,":[174],"Synthetic":[175],"dataset":[176],"generated":[178],"results":[180],"presented":[182],"considering":[183],"parameters":[186],"such":[187],"number":[189,197],"objects,":[191],"minsup,":[192],"value,":[196],"hops":[199],"any":[201],"computational":[204],"time.":[205],"Experiments":[206],"done":[208],"on":[209],"available":[210],"real-time":[211],"dataset,":[212,214],"taxi":[213],"too.":[215],"proved":[219],"be":[221],"worthy":[222],"understand":[226],"dynamics":[227],"objects":[231],"recommend":[234],"movements":[236],"constrained":[238],"networks.":[239]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}