{"id":"https://openalex.org/W2751778785","doi":"https://doi.org/10.1109/snpd.2017.8022719","title":"A novel passenger hotspots searching algorithm for taxis in urban area","display_name":"A novel passenger hotspots searching algorithm for taxis in urban area","publication_year":2017,"publication_date":"2017-06-01","ids":{"openalex":"https://openalex.org/W2751778785","doi":"https://doi.org/10.1109/snpd.2017.8022719","mag":"2751778785"},"language":"en","primary_location":{"id":"doi:10.1109/snpd.2017.8022719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd.2017.8022719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","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/A5108047157","display_name":"Yuhan Dong","orcid":"https://orcid.org/0000-0001-5275-1787"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuhan Dong","raw_affiliation_strings":["Graduate School at Shenzhen, Tsinghua Univ, China"],"affiliations":[{"raw_affiliation_string":"Graduate School at Shenzhen, Tsinghua Univ, China","institution_ids":["https://openalex.org/I3131625388"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041319107","display_name":"Siyuan Qian","orcid":"https://orcid.org/0009-0000-2278-8159"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siyuan Qian","raw_affiliation_strings":["Graduate School at Shenzhen, Tsinghua Univ, China"],"affiliations":[{"raw_affiliation_string":"Graduate School at Shenzhen, Tsinghua Univ, China","institution_ids":["https://openalex.org/I3131625388"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100323933","display_name":"Kai Zhang","orcid":"https://orcid.org/0000-0002-0505-3668"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Zhang","raw_affiliation_strings":["Graduate School at Shenzhen, Tsinghua Univ, China"],"affiliations":[{"raw_affiliation_string":"Graduate School at Shenzhen, Tsinghua Univ, China","institution_ids":["https://openalex.org/I3131625388"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002668391","display_name":"Yongzhi Zhai","orcid":"https://orcid.org/0000-0002-9554-6641"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongzhi Zhai","raw_affiliation_strings":["School of Commun. & Info. Eng., Xi'an Univ. of Posts & Telecommun, China"],"affiliations":[{"raw_affiliation_string":"School of Commun. & Info. Eng., Xi'an Univ. of Posts & Telecommun, China","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5108047157"],"corresponding_institution_ids":["https://openalex.org/I3131625388"],"apc_list":null,"apc_paid":null,"fwci":0.5265,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.71554057,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"175","last_page":"180"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9977999925613403,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9961000084877014,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/taxis","display_name":"Taxis","score":0.9593669772148132},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.740850031375885},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6764216423034668},{"id":"https://openalex.org/keywords/simulated-annealing","display_name":"Simulated annealing","score":0.6288893818855286},{"id":"https://openalex.org/keywords/affinity-propagation","display_name":"Affinity propagation","score":0.5597478747367859},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5258688926696777},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5065270662307739},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.4897487163543701},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46630656719207764},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.259242445230484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18199506402015686},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.149530291557312},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.1439538598060608},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09637561440467834}],"concepts":[{"id":"https://openalex.org/C183373512","wikidata":"https://www.wikidata.org/wiki/Q949618","display_name":"Taxis","level":2,"score":0.9593669772148132},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.740850031375885},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6764216423034668},{"id":"https://openalex.org/C126980161","wikidata":"https://www.wikidata.org/wiki/Q863783","display_name":"Simulated annealing","level":2,"score":0.6288893818855286},{"id":"https://openalex.org/C109659709","wikidata":"https://www.wikidata.org/wiki/Q3407504","display_name":"Affinity propagation","level":5,"score":0.5597478747367859},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5258688926696777},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5065270662307739},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.4897487163543701},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46630656719207764},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.259242445230484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18199506402015686},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.149530291557312},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.1439538598060608},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09637561440467834},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/snpd.2017.8022719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd.2017.8022719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1991190417","https://openalex.org/W2028113911","https://openalex.org/W2028618575","https://openalex.org/W2033626772","https://openalex.org/W2072957930","https://openalex.org/W2105772399","https://openalex.org/W2107634881","https://openalex.org/W2132968912","https://openalex.org/W2141136363","https://openalex.org/W2148959739","https://openalex.org/W2165169065","https://openalex.org/W2165232124","https://openalex.org/W2166926417","https://openalex.org/W2463678195","https://openalex.org/W2492209946","https://openalex.org/W2617391100","https://openalex.org/W2625777111","https://openalex.org/W2807054217"],"related_works":["https://openalex.org/W2731640799","https://openalex.org/W3145095895","https://openalex.org/W2594548639","https://openalex.org/W4387544810","https://openalex.org/W2978498151","https://openalex.org/W2782837293","https://openalex.org/W1946755446","https://openalex.org/W2388377527","https://openalex.org/W2114323843","https://openalex.org/W2751778785"],"abstract_inverted_index":{"Passenger":[0],"hotspots":[1,24,59],"searching":[2],"is":[3,34],"essential":[4],"to":[5,36,54],"increase":[6],"profits":[7],"for":[8,22],"taxis":[9,72],"drivers":[10],"in":[11,60],"urban":[12],"area.":[13],"In":[14,26,43],"this":[15],"paper,":[16],"we":[17,47],"propose":[18],"a":[19,30,61],"two-step":[20],"approach":[21,77],"pick-up":[23],"searching.":[25],"the":[27,38,44,56,75,79],"first":[28],"step,":[29,46],"traveling":[31,41],"similarity":[32,39],"model":[33],"built":[35],"quantify":[37],"of":[40,70,84],"behaviors.":[42],"second":[45],"utilize":[48],"affinity":[49],"propagation":[50],"and":[51],"simulated":[52],"annealing":[53],"identify":[55],"daily":[57],"passenger":[58],"selected":[62],"period.":[63],"Numerical":[64],"results":[65],"based":[66],"on":[67],"GPS":[68],"data":[69],"Manhattan":[71],"suggest":[73],"that":[74],"proposed":[76],"outperforms":[78],"traditional":[80],"spatio-temporal":[81],"clustering":[82],"regardless":[83],"buffer":[85],"radius.":[86]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
