{"id":"https://openalex.org/W3195393761","doi":"https://doi.org/10.1145/3468920.3468924","title":"Data-Driven Prediction of Key Attributes for Tobacco Products","display_name":"Data-Driven Prediction of Key Attributes for Tobacco Products","publication_year":2021,"publication_date":"2021-05-29","ids":{"openalex":"https://openalex.org/W3195393761","doi":"https://doi.org/10.1145/3468920.3468924","mag":"3195393761"},"language":"en","primary_location":{"id":"doi:10.1145/3468920.3468924","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3468920.3468924","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2021 3rd International Conference on Big Data Engineering","raw_type":"proceedings-article"},"type":"conference-paper","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/A5056260594","display_name":"Shunpeng Pang","orcid":null},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shunpeng Pang","raw_affiliation_strings":["Ocean University of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ocean University of China, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006745374","display_name":"Ruotong Hu","orcid":"https://orcid.org/0009-0008-4459-2155"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruotong Hu","raw_affiliation_strings":["Ocean University of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ocean University of China, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058718351","display_name":"Baoqi Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baoqi Guo","raw_affiliation_strings":["Qingdao New Star Software Consulting Co.,Ltd, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qingdao New Star Software Consulting Co.,Ltd, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104306172","display_name":"Junhua Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junhua Jia","raw_affiliation_strings":["Ocean University of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ocean University of China, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101020038","display_name":"Xiangqian Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangqian Ding","raw_affiliation_strings":["Ocean University of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ocean University of China, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032859417","display_name":"Shusong Yu","orcid":"https://orcid.org/0000-0003-1554-5313"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shusong Yu","raw_affiliation_strings":["Ocean University of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ocean University of China, China","institution_ids":["https://openalex.org/I59028903"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4682,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.53385362,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"25","last_page":"33"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.975600004196167,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.975600004196167,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9577999711036682,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.954800009727478,"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":0.7314328551292419},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7299516201019287},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.6316637992858887},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5812942385673523},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5201675891876221},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.513883113861084},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5032939314842224},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.49487799406051636},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.43032291531562805},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38918375968933105},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.356453001499176},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.22329387068748474},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.1946563422679901}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7314328551292419},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7299516201019287},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.6316637992858887},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5812942385673523},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5201675891876221},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.513883113861084},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5032939314842224},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.49487799406051636},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.43032291531562805},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38918375968933105},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.356453001499176},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.22329387068748474},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.1946563422679901},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3468920.3468924","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3468920.3468924","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2021 3rd International Conference on Big Data Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1003889152","https://openalex.org/W1806891645","https://openalex.org/W1979606776","https://openalex.org/W2097998348","https://openalex.org/W2264803961","https://openalex.org/W2276995557","https://openalex.org/W2367620142","https://openalex.org/W2369396938","https://openalex.org/W2529099292","https://openalex.org/W2573587735","https://openalex.org/W2587586954","https://openalex.org/W2591829606","https://openalex.org/W2606906085","https://openalex.org/W2754252319","https://openalex.org/W2776022701","https://openalex.org/W2782968911","https://openalex.org/W2783204403","https://openalex.org/W2789364533","https://openalex.org/W2792326773","https://openalex.org/W2795353455","https://openalex.org/W2885169504","https://openalex.org/W2889220424","https://openalex.org/W2894821558","https://openalex.org/W2905238323","https://openalex.org/W2911585043","https://openalex.org/W2911964244","https://openalex.org/W2913702122","https://openalex.org/W2914448491","https://openalex.org/W2946181338","https://openalex.org/W2988646256","https://openalex.org/W3035284005","https://openalex.org/W3081122106"],"related_works":["https://openalex.org/W2118717649","https://openalex.org/W2413243053","https://openalex.org/W410723623","https://openalex.org/W2015341305","https://openalex.org/W2035068594","https://openalex.org/W4225593417","https://openalex.org/W2573498121","https://openalex.org/W3022298670","https://openalex.org/W3160494304","https://openalex.org/W3006162251"],"abstract_inverted_index":{"Draw":[0],"resistance":[1,57],"of":[2,7,11,27,59,81,85,125,155],"the":[3,8,25,40,54,69,77,82,86,90,126,140,153,161,185],"cigarette":[4,28,41,55,106],"is":[5,66],"one":[6],"critical":[9],"attributes":[10],"tobacco":[12],"products.":[13],"It":[14,148],"directly":[15],"affects":[16],"consumers'":[17],"health":[18],"and":[19,32,52,72,79,103,113,170,178],"has":[20,167,179],"a":[21,47,63,105],"close":[22],"relationship":[23],"with":[24,89],"release":[26],"tar,":[29],"smokes":[30],"nicotine,":[31],"carbon":[33],"monoxide":[34],"volume.":[35],"Therefore,":[36],"to":[37,142,183],"better":[38],"monitor":[39],"draw":[42,56],"resistance,":[43],"we":[44,95],"have":[45],"developed":[46],"monitoring":[48],"system":[49],"for":[50,68,110,130],"forecasting":[51],"tracking":[53],"instead":[58],"random":[60],"sampling":[61],"by":[62],"manual":[64],"that":[65,160],"time-consuming":[67],"security":[70],"inspector":[71],"low":[73],"accuracy.":[74],"To":[75],"realize":[76],"interconnection":[78],"fusion":[80,146],"multi-sensors":[83],"data":[84,107,121,145],"production":[87,92,116],"process":[88,93],"upper":[91],"data,":[94],"used":[96],"\"PTC":[97],"Thingworx\"":[98],"as":[99],"an":[100,180],"IIoT":[101],"platform,":[102],"designed":[104],"collection":[108],"program":[109],"getting":[111],"big":[112],"high-speed":[114],"real-time":[115],"data.":[117],"We":[118,132],"performed":[119],"pre-processing":[120],"work":[122],"in":[123,139,164],"terms":[124],"customized":[127],"time":[128],"window":[129],"monitoring.":[131],"first":[133],"introduce":[134],"recurrent":[135],"neural":[136],"networks":[137],"(RNNs)":[138],"field":[141],"forecast-based":[143],"multi-sensor":[144],"approaches.":[147],"can":[149,174],"be":[150],"seen":[151],"from":[152],"test":[154],"various":[156],"metrics":[157],"on":[158],"datasets":[159],"method":[162],"proposed":[163],"this":[165],"paper":[166],"strong":[168],"robustness":[169],"generalizability.":[171],"The":[172],"technique":[173],"completely":[175],"replace":[176],"labor":[177],"outstanding":[181],"contribution":[182],"replacing":[184],"monitors.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
