{"id":"https://openalex.org/W2566478918","doi":"https://doi.org/10.1109/itsc.2016.7795968","title":"Heuristic optimizations for high-speed low-latency online map matching with probabilistic sequence models","display_name":"Heuristic optimizations for high-speed low-latency online map matching with probabilistic sequence models","publication_year":2016,"publication_date":"2016-11-01","ids":{"openalex":"https://openalex.org/W2566478918","doi":"https://doi.org/10.1109/itsc.2016.7795968","mag":"2566478918"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2016.7795968","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2016.7795968","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-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/A5051180586","display_name":"George Rosario Jagadeesh","orcid":"https://orcid.org/0000-0003-0166-0409"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"George R. Jagadeesh","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070475093","display_name":"Thambipillai Srikanthan","orcid":"https://orcid.org/0000-0003-3664-4345"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Thambipillai Srikanthan","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5051180586"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":1.2948,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.82072539,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2565","last_page":"2570"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9987000226974487,"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":0.9987000226974487,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9947999715805054,"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":0.9840999841690063,"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/computer-science","display_name":"Computer science","score":0.7737674117088318},{"id":"https://openalex.org/keywords/viterbi-algorithm","display_name":"Viterbi algorithm","score":0.7145982980728149},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.688861608505249},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6236510872840881},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5971105694770813},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5135633945465088},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4593300223350525},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.435426265001297},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4338809847831726},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24662423133850098}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7737674117088318},{"id":"https://openalex.org/C60582962","wikidata":"https://www.wikidata.org/wiki/Q83886","display_name":"Viterbi algorithm","level":3,"score":0.7145982980728149},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.688861608505249},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6236510872840881},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5971105694770813},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5135633945465088},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4593300223350525},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.435426265001297},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4338809847831726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24662423133850098},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/itsc.2016.7795968","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2016.7795968","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},{"id":"pmh:oai:dr.ntu.edu.sg:10356/145765","is_oa":false,"landing_page_url":"https://hdl.handle.net/10356/145765","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"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":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1939940937","https://openalex.org/W1953838480","https://openalex.org/W1991133427","https://openalex.org/W1996573126","https://openalex.org/W2022739057","https://openalex.org/W2059289850","https://openalex.org/W2084634989","https://openalex.org/W2128641067","https://openalex.org/W2135822894","https://openalex.org/W2139034093","https://openalex.org/W2145022515","https://openalex.org/W2166771065","https://openalex.org/W2169528473","https://openalex.org/W2295096861","https://openalex.org/W2401054706","https://openalex.org/W4237835075","https://openalex.org/W6665367523"],"related_works":["https://openalex.org/W2136652457","https://openalex.org/W2169849734","https://openalex.org/W2116722627","https://openalex.org/W2129150969","https://openalex.org/W2236912844","https://openalex.org/W1975869217","https://openalex.org/W2401728283","https://openalex.org/W2383829109","https://openalex.org/W2379938888","https://openalex.org/W2386035178"],"abstract_inverted_index":{"The":[0],"computation":[1],"speed":[2,68,110],"and":[3,19,60,69,202],"output":[4,164,203],"latency":[5,139,204],"of":[6,26,42,78,82,96,140,165,173,176,181,208],"map":[7,44,84],"matching":[8,45,85],"are":[9,48],"important":[10],"considerations":[11],"when":[12],"processing":[13],"location":[14,190],"data,":[15,21],"especially":[16],"smartphone-generated":[17],"noisy":[18],"sparse":[20],"from":[22],"a":[23,89,134,153,156,177],"large":[24],"number":[25,95],"users":[27],"for":[28,76,91,136],"real-time":[29],"transportation":[30],"applications.":[31],"In":[32],"this":[33],"paper,":[34],"we":[35,87,109],"examine":[36],"the":[37,40,79,93,104,112,119,129,138,141,147,162,174,182,194,199],"factors":[38],"affecting":[39],"efficiency":[41],"online":[43],"algorithms":[46],"that":[47,126,193],"based":[49,169],"on":[50,170],"probabilistic":[51,83,105],"sequence":[52,106,151],"models":[53],"such":[54,97],"as":[55],"Hidden":[56],"Markov":[57],"Models":[58],"(HMM)":[59],"present":[61,133],"several":[62],"heuristic":[63,195],"optimizations":[64,196],"to":[65,122,145],"improve":[66],"their":[67],"latency.":[70],"As":[71],"shortest":[72,114],"path":[73,115],"computations":[74,98,116],"account":[75],"most":[77,148,184],"running":[80,200],"time":[81,201],"algorithms,":[86],"propose":[88],"method":[90],"reducing":[92,137],"total":[94],"by":[99,117],"pruning":[100],"unlikely":[101],"states":[102],"in":[103,152],"model.":[107,158],"Furthermore,":[108],"up":[111],"one-to-many":[113],"limiting":[118],"search":[120],"space":[121],"an":[123,171],"elliptical":[124],"area":[125],"encompasses":[127],"all":[128],"targeted":[130],"destinations.":[131],"We":[132],"technique":[135,160],"Viterbi":[142],"algorithm":[143],"used":[144],"find":[146],"likely":[149,185],"state":[150,167,178],"HMM":[154],"or":[155],"similar":[157],"This":[159],"enables":[161],"early":[163],"partial":[166],"sequences":[168],"estimate":[172],"probability":[175],"being":[179],"part":[180],"eventual":[183],"sequence.":[186],"Experiments":[187],"using":[188],"real-world":[189],"data":[191],"show":[192],"significantly":[197],"reduce":[198],"with":[205],"negligible":[206],"loss":[207],"accuracy.":[209]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}