{"id":"https://openalex.org/W2548164267","doi":"https://doi.org/10.1109/sahcn.2016.7733025","title":"Verification of User-Reported Context Claims with Context Correlation Model","display_name":"Verification of User-Reported Context Claims with Context Correlation Model","publication_year":2016,"publication_date":"2016-06-01","ids":{"openalex":"https://openalex.org/W2548164267","doi":"https://doi.org/10.1109/sahcn.2016.7733025","mag":"2548164267"},"language":"en","primary_location":{"id":"doi:10.1109/sahcn.2016.7733025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sahcn.2016.7733025","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 13th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)","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/A5018486648","display_name":"Jindan Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jindan Zhu","raw_affiliation_strings":["Department of Computer Science, University of California at Davis, Davis, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California at Davis, Davis, CA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012908666","display_name":"Anjan Goswami","orcid":null},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anjan Goswami","raw_affiliation_strings":["Department of Computer Science, University of California at Davis, Davis, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California at Davis, Davis, CA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088588796","display_name":"Kyu-Han Kim","orcid":"https://orcid.org/0000-0002-8247-225X"},"institutions":[{"id":"https://openalex.org/I1324840837","display_name":"Hewlett-Packard (United States)","ror":"https://ror.org/059rn9488","country_code":"US","type":"company","lineage":["https://openalex.org/I1324840837"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyu-Han Kim","raw_affiliation_strings":["Hewlett-Packard Laboratories, Palo Alto, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hewlett-Packard Laboratories, Palo Alto, CA","institution_ids":["https://openalex.org/I1324840837"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086439160","display_name":"Prasant Mohapatra","orcid":"https://orcid.org/0000-0002-2768-5308"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prasant Mohapatra","raw_affiliation_strings":["Department of Computer Science, University of California at Davis, Davis, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California at Davis, Davis, CA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12788474,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10927","display_name":"Access Control and Trust","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/context","display_name":"Context (archaeology)","score":0.7807953953742981},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7241495847702026},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5876641869544983},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5490522384643555},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5360434651374817},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.49368152022361755},{"id":"https://openalex.org/keywords/incentive","display_name":"Incentive","score":0.4918954372406006},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.48802486062049866},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.48641085624694824},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4389420747756958},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.427407443523407},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4032916724681854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3990338444709778},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.37895140051841736},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.33303406834602356},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.1129077672958374},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.104594886302948},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.07837066054344177}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.7807953953742981},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7241495847702026},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5876641869544983},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5490522384643555},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5360434651374817},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.49368152022361755},{"id":"https://openalex.org/C29122968","wikidata":"https://www.wikidata.org/wiki/Q1414816","display_name":"Incentive","level":2,"score":0.4918954372406006},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.48802486062049866},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.48641085624694824},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4389420747756958},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.427407443523407},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4032916724681854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3990338444709778},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.37895140051841736},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.33303406834602356},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.1129077672958374},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.104594886302948},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.07837066054344177},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sahcn.2016.7733025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sahcn.2016.7733025","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 13th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W184229337","https://openalex.org/W1542792105","https://openalex.org/W1566045017","https://openalex.org/W1802230853","https://openalex.org/W1817561967","https://openalex.org/W2003028314","https://openalex.org/W2003684739","https://openalex.org/W2031363638","https://openalex.org/W2035112165","https://openalex.org/W2036110521","https://openalex.org/W2063397598","https://openalex.org/W2075036079","https://openalex.org/W2082681648","https://openalex.org/W2096158370","https://openalex.org/W2101782549","https://openalex.org/W2108836391","https://openalex.org/W2109431634","https://openalex.org/W2116636079","https://openalex.org/W2126333155","https://openalex.org/W2130416704","https://openalex.org/W2131294487","https://openalex.org/W2143554828","https://openalex.org/W2145060596","https://openalex.org/W2146322883","https://openalex.org/W2155189155","https://openalex.org/W2165005140","https://openalex.org/W2167804035","https://openalex.org/W2979006918","https://openalex.org/W3133236490","https://openalex.org/W4299515571","https://openalex.org/W6633761756","https://openalex.org/W6638736948","https://openalex.org/W6666026808","https://openalex.org/W6679606034","https://openalex.org/W6680983478"],"related_works":["https://openalex.org/W2407375987","https://openalex.org/W2505726097","https://openalex.org/W2950975704","https://openalex.org/W2010643158","https://openalex.org/W3049691116","https://openalex.org/W2106867672","https://openalex.org/W4310268968","https://openalex.org/W3081214562","https://openalex.org/W2053745677","https://openalex.org/W2189378472"],"abstract_inverted_index":{"Context-aware":[0],"services":[1],"nowadays":[2],"offer":[3],"incentive":[4],"to":[5,15,69,107,121],"user-reported":[6],"context":[7,20,33,44,58,83,95,125,154],"information":[8,45],",":[9],"which":[10],"inevitably":[11],"solicits":[12],"malicious":[13],"users":[14],"cheat":[16],"by":[17],"submitting":[18],"fabricated":[19],"claims.":[21],"Conventional":[22],"countermeasures":[23],"based":[24],"on":[25,31,132],"Trusted":[26],"Computing":[27],"Base":[28],"typically":[29],"focus":[30],"particular":[32],"of":[34,40,43,66,93,124,141,150],"interest,":[35],"while":[36],"disregarding":[37],"the":[38,47,73,82,99,105,109,148],"availability":[39],"various":[41],"types":[42,123],"and":[46,80,96,117,136,146],"intrinsic":[48],"correlation":[49,84],"among":[50],"them.":[51],"In":[52],"this":[53],"work":[54],"we":[55],"propose":[56],"a":[57,86,90,127],"claim":[59,91],"verification":[60,113],"scheme":[61,100,152],"that":[62],"interrogates":[63],"correlated":[64],"contexts":[65],"multiple":[67],"dimensions":[68],"corroborate":[70],"or":[71],"contradict":[72],"reported":[74,94,110],"context.":[75,111],"Specifically,":[76],"it":[77],"first":[78],"learns":[79],"models":[81],"with":[85,104,126],"Bayesian":[87,102],"Multinet.":[88],"Given":[89],"consisting":[92],"witnessing":[97],"evidence,":[98],"performs":[101],"inference":[103],"evidence":[106],"verify":[108],"The":[112],"process":[114],"is":[115],"light-weight,":[116],"can":[118],"be":[119],"applied":[120],"arbitrary":[122],"single":[128],"model":[129],"learnt.":[130],"Evaluations":[131],"Reality":[133],"Mining":[134],"dataset":[135,138],"synthetic":[137],"validates":[139],"choice":[140],"Multinet":[142],"for":[143],"data":[144],"modeling,":[145],"demonstrate":[147],"feasibility":[149],"our":[151],"in":[153],"verification.":[155]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
