{"id":"https://openalex.org/W2967249106","doi":"https://doi.org/10.1145/3342515","title":"Towards Profit Optimization During Online Participant Selection in Compressive Mobile Crowdsensing","display_name":"Towards Profit Optimization During Online Participant Selection in Compressive Mobile Crowdsensing","publication_year":2019,"publication_date":"2019-08-15","ids":{"openalex":"https://openalex.org/W2967249106","doi":"https://doi.org/10.1145/3342515","mag":"2967249106"},"language":"en","primary_location":{"id":"doi:10.1145/3342515","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3342515","pdf_url":null,"source":{"id":"https://openalex.org/S170502224","display_name":"ACM Transactions on Sensor Networks","issn_l":"1550-4859","issn":["1550-4859","1550-4867"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Sensor Networks","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/A5101954640","display_name":"Yueyue Chen","orcid":"https://orcid.org/0000-0001-6979-1144"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueyue Chen","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-6979-1144","affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032623398","display_name":"Deke Guo","orcid":"https://orcid.org/0000-0003-4894-5540"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]},{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deke Guo","raw_affiliation_strings":["National University of Defense Technology, China and Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, China and Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743","https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086666436","display_name":"Md Zakirul Alam Bhuiyan","orcid":"https://orcid.org/0000-0002-9513-9990"},"institutions":[{"id":"https://openalex.org/I164389053","display_name":"Fordham University","ror":"https://ror.org/03qnxaf80","country_code":"US","type":"education","lineage":["https://openalex.org/I164389053"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"MD Zakirul Alam Bhuiyan","raw_affiliation_strings":["Fordham University, NewYork, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fordham University, NewYork, USA","institution_ids":["https://openalex.org/I164389053"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110466855","display_name":"Ming Xu","orcid":"https://orcid.org/0000-0001-6979-1144"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Xu","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-6979-1144","affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100386726","display_name":"Guojun Wang","orcid":"https://orcid.org/0000-0001-9875-4182"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guojun Wang","raw_affiliation_strings":["Guangzhou University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041894655","display_name":"Pin Lv","orcid":"https://orcid.org/0000-0002-3425-9913"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pin Lv","raw_affiliation_strings":["Guangxi University, Nanning, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5746,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.86823513,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"15","issue":"4","first_page":"1","last_page":"29"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.98580002784729,"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/crowdsensing","display_name":"Crowdsensing","score":0.8898217678070068},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8364952206611633},{"id":"https://openalex.org/keywords/profit","display_name":"Profit (economics)","score":0.6430598497390747},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5067358613014221},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44805172085762024},{"id":"https://openalex.org/keywords/payment","display_name":"Payment","score":0.44127514958381653},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4227690100669861},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"Crowdsourcing","score":0.41226714849472046},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39299434423446655},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.2038782238960266}],"concepts":[{"id":"https://openalex.org/C2780821482","wikidata":"https://www.wikidata.org/wiki/Q25381721","display_name":"Crowdsensing","level":2,"score":0.8898217678070068},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8364952206611633},{"id":"https://openalex.org/C181622380","wikidata":"https://www.wikidata.org/wiki/Q26911","display_name":"Profit (economics)","level":2,"score":0.6430598497390747},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5067358613014221},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44805172085762024},{"id":"https://openalex.org/C145097563","wikidata":"https://www.wikidata.org/wiki/Q1148747","display_name":"Payment","level":2,"score":0.44127514958381653},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4227690100669861},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.41226714849472046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39299434423446655},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2038782238960266},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3342515","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3342515","pdf_url":null,"source":{"id":"https://openalex.org/S170502224","display_name":"ACM Transactions on Sensor Networks","issn_l":"1550-4859","issn":["1550-4859","1550-4867"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Sensor Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G4500808531","display_name":null,"funder_award_id":"61772544, 61872372, 61672195, and 61632009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6200922333","display_name":null,"funder_award_id":"2017A03030800","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W79201747","https://openalex.org/W1595564818","https://openalex.org/W1970266075","https://openalex.org/W1971402834","https://openalex.org/W2042462978","https://openalex.org/W2047963480","https://openalex.org/W2075816638","https://openalex.org/W2083868427","https://openalex.org/W2123140882","https://openalex.org/W2125826911","https://openalex.org/W2144364471","https://openalex.org/W2144475703","https://openalex.org/W2146616964","https://openalex.org/W2165178985","https://openalex.org/W2329460483","https://openalex.org/W2430546716","https://openalex.org/W2430704425","https://openalex.org/W2471528185","https://openalex.org/W2489627439","https://openalex.org/W2491777287","https://openalex.org/W2535034338","https://openalex.org/W2535723296","https://openalex.org/W2538733971","https://openalex.org/W2606709877","https://openalex.org/W2609560235","https://openalex.org/W2613582265","https://openalex.org/W2614598347","https://openalex.org/W2682403416","https://openalex.org/W2708015072","https://openalex.org/W2734175605","https://openalex.org/W2735047435","https://openalex.org/W2737157722","https://openalex.org/W2763801300","https://openalex.org/W2765580447","https://openalex.org/W2789572951","https://openalex.org/W2792960831","https://openalex.org/W2809254512","https://openalex.org/W2883923456","https://openalex.org/W2914701924","https://openalex.org/W2963044698","https://openalex.org/W2999946671"],"related_works":["https://openalex.org/W3032998312","https://openalex.org/W4384486036","https://openalex.org/W135177976","https://openalex.org/W1503094549","https://openalex.org/W2337920774","https://openalex.org/W2886410948","https://openalex.org/W2025875869","https://openalex.org/W4318823662","https://openalex.org/W2896200027","https://openalex.org/W2603064225"],"abstract_inverted_index":{"A":[0,15,174],"mobile":[1],"crowdsensing":[2],"(MCS)":[3],"platform":[4],"motivates":[5],"employing":[6],"participants":[7,37,145,230],"from":[8],"the":[9,21,24,27,34,40,47,50,64,69,96,100,104,108,119,136,140,150,156,163,171,186,193,210,229,236],"crowd":[10],"to":[11,19,36,62,68,114,181],"complete":[12],"sensing":[13,31,97,157],"tasks.":[14],"crucial":[16],"problem":[17],"is":[18,60,107,166,179,189],"maximize":[20],"profit":[22,48,234],"of":[23,29,74,99,143,159],"platform,":[25],"i.e.,":[26],"charge":[28],"a":[30,129,232],"task":[32],"minus":[33],"payments":[35],"that":[38,217],"execute":[39],"task.":[41],"In":[42,76],"this":[43,116,183],"article,":[44],"we":[45,204],"improve":[46],"via":[49],"data":[51],"reconstruction":[52,65],"method,":[53],"which":[54,168],"brings":[55],"new":[56],"challenges,":[57],"because":[58],"it":[59,170],"hard":[61],"predict":[63],"quality":[66,125],"due":[67],"dynamic":[70],"features":[71],"and":[72,121,128,139,191,196,224],"mobility":[73],"participants.":[75],"particular,":[77],"two":[78],"Profit-driven":[79],"Online":[80],"Participant":[81],"Selection":[82],"(POPS)":[83],"problems":[84],"under":[85],"different":[86,101,160],"situations":[87],"are":[88,112,133,146,198,221],"studied":[89],"in":[90,135,149,200],"our":[91,218],"work:":[92],"(1)":[93],"for":[94,154,235],"S-POPS,":[95],"cost":[98,158],"parts":[102,161],"within":[103,162],"target":[105,164],"area":[106,165],"Same.":[109],"Two":[110],"mechanisms":[111,220],"designed":[113],"tackle":[115],"problem,":[117,184],"including":[118],"ProSC":[120],"ProSC+.":[122],"An":[123],"exponential-based":[124],"estimation":[126],"method":[127],"repetitive":[130],"cross-validation":[131],"algorithm":[132],"combined":[134],"former":[137],"mechanism,":[138],"spatial":[141],"distribution":[142,197],"selected":[144],"further":[147],"discussed":[148],"latter":[151],"mechanism;":[152],"(2)":[153],"V-POPS,":[155],"Various,":[167],"makes":[169],"NP-hard":[172],"problem.":[173],"heuristic":[175],"mechanism":[176],"called":[177],"ProSCx":[178],"proposed":[180,219],"solve":[182],"where":[185],"searching":[187],"space":[188],"narrowed":[190],"both":[192],"participant":[194],"quantity":[195],"optimized":[199],"each":[201],"slot.":[202],"Finally,":[203],"conduct":[205],"comprehensive":[206],"evaluations":[207],"based":[208],"on":[209],"real-world":[211],"datasets.":[212],"The":[213],"experimental":[214],"results":[215],"demonstrate":[216],"more":[222],"effective":[223],"efficient":[225],"than":[226],"baselines,":[227],"selecting":[228],"with":[231],"larger":[233],"platform.":[237]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
