{"id":"https://openalex.org/W2053056246","doi":"https://doi.org/10.1109/ccece.2014.6901141","title":"Multiple classifications for detecting Spam email by novel consultation algorithm","display_name":"Multiple classifications for detecting Spam email by novel consultation algorithm","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2053056246","doi":"https://doi.org/10.1109/ccece.2014.6901141","mag":"2053056246"},"language":"en","primary_location":{"id":"doi:10.1109/ccece.2014.6901141","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccece.2014.6901141","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE)","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/A5002055824","display_name":"Mohammad-Ali Oveis-Gharan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210120856","display_name":"University College of Nabi Akram","ror":"https://ror.org/02kqbjv38","country_code":"IR","type":"education","lineage":["https://openalex.org/I4210120856"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Mohammad-Ali Oveis-Gharan","raw_affiliation_strings":["Faculty of engineering, University college of Nabi Akram, Tabriz, Iran"],"affiliations":[{"raw_affiliation_string":"Faculty of engineering, University college of Nabi Akram, Tabriz, Iran","institution_ids":["https://openalex.org/I4210120856"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042529202","display_name":"Kaamran Raahemifar","orcid":"https://orcid.org/0000-0002-9835-7897"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Kaamran Raahemifar","raw_affiliation_strings":["Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada","Electrical and Computer Engineering, Ryerson University, 350 Victoria St, Toronto, ON M5B 2K3 Canada"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada","institution_ids":["https://openalex.org/I530967"]},{"raw_affiliation_string":"Electrical and Computer Engineering, Ryerson University, 350 Victoria St, Toronto, ON M5B 2K3 Canada","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5002055824"],"corresponding_institution_ids":["https://openalex.org/I4210120856"],"apc_list":null,"apc_paid":null,"fwci":3.1556,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.92758377,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11644","display_name":"Spam and Phishing Detection","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.998199999332428,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9977999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7851279377937317},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.595766544342041},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5392393469810486},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4769498407840729},{"id":"https://openalex.org/keywords/electronic-mail","display_name":"Electronic mail","score":0.434373676776886},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3921087980270386},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3535304069519043},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33461111783981323},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.3222205638885498}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7851279377937317},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.595766544342041},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5392393469810486},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4769498407840729},{"id":"https://openalex.org/C3020028006","wikidata":"https://www.wikidata.org/wiki/Q9158","display_name":"Electronic mail","level":2,"score":0.434373676776886},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3921087980270386},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3535304069519043},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33461111783981323},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3222205638885498},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccece.2014.6901141","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccece.2014.6901141","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1973644085","https://openalex.org/W2024858689","https://openalex.org/W2055043826","https://openalex.org/W2071254787","https://openalex.org/W2100170134","https://openalex.org/W2185177373","https://openalex.org/W2340809277","https://openalex.org/W6686146533"],"related_works":["https://openalex.org/W2804364458","https://openalex.org/W4298130764","https://openalex.org/W2132641928","https://openalex.org/W2090259340","https://openalex.org/W4310225030","https://openalex.org/W2083665254","https://openalex.org/W2393816671","https://openalex.org/W1534720161","https://openalex.org/W2804957450","https://openalex.org/W2942177010"],"abstract_inverted_index":{"Much":[0],"work":[1],"and":[2,22,32,107,121,136,159],"many":[3,68],"transactions":[4],"these":[5,87],"days":[6],"are":[7,103],"done":[8],"via":[9],"email.":[10,83,142],"Email":[11],"is":[12,52,58],"a":[13,41,55,128,147],"powerful":[14],"tool":[15],"for":[16,64],"communication":[17],"that":[18,51,102],"saves":[19],"both":[20],"time":[21],"cost.":[23],"However,":[24,84],"due":[25],"to":[26,40,47,73,99,131,137],"the":[27,34,115,118],"growth":[28],"of":[29,36,44,86,95,117,146,156],"social":[30],"networks":[31],"advertisers,":[33],"number":[35],"unwanted":[37],"emails":[38],"sent":[39,53],"cumulative":[42],"mass":[43],"users":[45],"continues":[46],"grow.":[48],"Junk":[49],"email":[50,78,135],"in":[54],"bulk":[56],"fashion":[57],"called":[59],"UBE":[60],"or":[61,76,81],"Spam":[62,77,139],"email,":[63],"short.":[65],"To":[66],"date":[67],"algorithms":[69,88],"have":[70,97],"been":[71,90],"devised":[72],"flag":[74,133],"junk":[75,134],"from":[79,140],"legitimate":[80],"Ham":[82,141],"none":[85],"has":[89],"100%":[91],"accurate.":[92],"Recent":[93],"studies":[94],"clustering":[96],"pointed":[98],"hybrid":[100],"methods":[101],"powerful,":[104],"stable,":[105],"accurate,":[106],"more":[108],"common":[109],"than":[110],"previous":[111],"ones.":[112],"Inspired":[113],"by":[114,153],"processes":[116],"Public":[119],"Consultation":[120],"Voting":[122],"System,":[123],"this":[124],"paper":[125],"will":[126,151],"present":[127],"novel":[129],"algorithm":[130,150],"accurately":[132],"separate":[138],"The":[143],"error":[144],"rate":[145],"single":[148],"optimization":[149],"improve":[152],"39%":[154],"using":[155],"our":[157],"consultation":[158],"voting":[160],"(CAV)":[161],"algorithm.":[162]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}