{"id":"https://openalex.org/W4408696702","doi":"https://doi.org/10.1109/itsc58415.2024.10920083","title":"Knowledge Refinement: An Interpretable Analytics for Travel Behaviors Based on Knowledge Automation","display_name":"Knowledge Refinement: An Interpretable Analytics for Travel Behaviors Based on Knowledge Automation","publication_year":2024,"publication_date":"2024-09-24","ids":{"openalex":"https://openalex.org/W4408696702","doi":"https://doi.org/10.1109/itsc58415.2024.10920083"},"language":"en","primary_location":{"id":"doi:10.1109/itsc58415.2024.10920083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc58415.2024.10920083","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 27th 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/A5025706580","display_name":"Peijun Ye","orcid":"https://orcid.org/0000-0001-9987-9016"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peijun Ye","raw_affiliation_strings":["Institute of Automation,State Key Laboratory of Multimodal Artificial Intelligence Systems, Chinese Academy of Sciences,Beijing,China,100190"],"affiliations":[{"raw_affiliation_string":"Institute of Automation,State Key Laboratory of Multimodal Artificial Intelligence Systems, Chinese Academy of Sciences,Beijing,China,100190","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113234606","display_name":"Renrui Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renrui Zhang","raw_affiliation_strings":["Institute of Automation,State Key Laboratory of Multimodal Artificial Intelligence Systems, Chinese Academy of Sciences,Beijing,China,100190"],"affiliations":[{"raw_affiliation_string":"Institute of Automation,State Key Laboratory of Multimodal Artificial Intelligence Systems, Chinese Academy of Sciences,Beijing,China,100190","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108562153","display_name":"Shichao Ge","orcid":"https://orcid.org/0000-0002-1289-0464"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shichao Ge","raw_affiliation_strings":["School of Automation and Intelligence, Beijing Jiaotong University,Beijing,China,100044"],"affiliations":[{"raw_affiliation_string":"School of Automation and Intelligence, Beijing Jiaotong University,Beijing,China,100044","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025706580"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"],"apc_list":null,"apc_paid":null,"fwci":0.3626,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.71476008,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"609","last_page":"614"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.8622000217437744,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.8622000217437744,"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/T11719","display_name":"Data Quality and Management","score":0.8468000292778015,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision 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":0.8367999792098999,"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":0.7492047548294067},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.6479822397232056},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.6439003944396973},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4986844062805176},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.3852486312389374},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10306599736213684}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7492047548294067},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.6479822397232056},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.6439003944396973},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4986844062805176},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.3852486312389374},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10306599736213684},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc58415.2024.10920083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc58415.2024.10920083","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2506547696","display_name":null,"funder_award_id":"62076237","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2345172924","https://openalex.org/W2624151630","https://openalex.org/W2777363140","https://openalex.org/W2900694626","https://openalex.org/W2901213466","https://openalex.org/W2953151079","https://openalex.org/W3002423105","https://openalex.org/W3030946377","https://openalex.org/W3082474082","https://openalex.org/W3091419934","https://openalex.org/W3135930035","https://openalex.org/W3177968589","https://openalex.org/W4289886757","https://openalex.org/W4365141128","https://openalex.org/W4389359760","https://openalex.org/W4391461009","https://openalex.org/W6639086533"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Travel":[0],"behavioral":[1,31],"analysis":[2],"is":[3,98],"crucial":[4],"to":[5,24],"the":[6,27,54,90,112,117,140],"demand":[7],"computation,":[8],"which":[9],"underpins":[10],"traffic":[11,123],"planning":[12],"and":[13,18,52,86,97],"optimization":[14],"of":[15,46,56,92,104,121],"transportation":[16,106],"management":[17],"control.":[19],"While":[20],"traditional":[21,127],"methods":[22],"seek":[23],"descriptively":[25],"learn":[26],"travel":[28,70],"patterns":[29],"through":[30],"models":[32],"as":[33,35,77,139],"well":[34],"big":[36],"data":[37,103],"from":[38],"multiple":[39],"sources,":[40],"they":[41],"perform":[42],"weak":[43],"predictive":[44],"ability":[45,120],"system's":[47],"evolutionary":[48],"features.":[49],"To":[50],"model":[51],"analyze":[53],"dynamics":[55,135],"such":[57,138],"cyber":[58],"physical":[59],"social":[60],"systems,":[61,96],"this":[62],"paper":[63],"proposes":[64],"an":[65],"interpretable":[66],"analytical":[67],"method":[68],"for":[69,89],"behaviors":[71],"based":[72],"on":[73],"knowledge":[74,78],"automation":[75],"(named":[76],"refinement).":[79],"The":[80],"new":[81],"approach":[82,113],"provides":[83],"a":[84],"feasible":[85],"reliable":[87],"methodology":[88],"analytics":[91],"heterogenous":[93],"human":[94],"participated":[95],"validated":[99],"using":[100],"one":[101],"month's":[102],"public":[105],"in":[107],"Beijing.":[108],"Results":[109],"indicate":[110],"that":[111],"not":[114],"only":[115],"has":[116],"state-of-the-art":[118],"\u201creproductive\u201d":[119],"actual":[122],"flows":[124],"compare":[125],"with":[126,136],"methods,":[128],"but":[129],"also":[130],"can":[131],"further":[132],"reveal":[133],"systemic":[134],"semantics":[137],"stable":[141],"or":[142],"divergent":[143],"regions.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}