{"id":"https://openalex.org/W1964193191","doi":"https://doi.org/10.1109/iscas.2012.6272177","title":"Content-based spam filtering using hybrid generative discriminative learning of both textual and visual features","display_name":"Content-based spam filtering using hybrid generative discriminative learning of both textual and visual features","publication_year":2012,"publication_date":"2012-05-01","ids":{"openalex":"https://openalex.org/W1964193191","doi":"https://doi.org/10.1109/iscas.2012.6272177","mag":"1964193191"},"language":"en","primary_location":{"id":"doi:10.1109/iscas.2012.6272177","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2012.6272177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Symposium on Circuits and Systems","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/A5076244418","display_name":"Ola Amayri","orcid":"https://orcid.org/0000-0003-3672-5997"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ola Amayri","raw_affiliation_strings":["Electrical and Computer Engineering Department, Concordia University, Montreal, Canada","Electrical and Computer Engineering Department Concordia University Montreal, Canada, H3G 2W1"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, Concordia University, Montreal, Canada","institution_ids":["https://openalex.org/I60158472"]},{"raw_affiliation_string":"Electrical and Computer Engineering Department Concordia University Montreal, Canada, H3G 2W1","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090600716","display_name":"Nizar Bouguila","orcid":"https://orcid.org/0000-0001-7224-7940"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Nizar Bouguila","raw_affiliation_strings":["Concordia Institute for Information Systems Engineering, Concordia University, Montreal, Canada","Concordia Institute for Information Systems Engineering, Concordia University, Montreal, Canada, H3G 2W1"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Concordia Institute for Information Systems Engineering, Concordia University, Montreal, Canada","institution_ids":["https://openalex.org/I60158472"]},{"raw_affiliation_string":"Concordia Institute for Information Systems Engineering, Concordia University, Montreal, Canada, H3G 2W1","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":0.9609,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.72807018,"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":"862","last_page":"865"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9998999834060669,"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":0.9998999834060669,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.989300012588501,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.9083738327026367},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7535125017166138},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7318565845489502},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6994805335998535},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5781083703041077},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5638365149497986},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.556513249874115},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.524504542350769},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46991291642189026}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9083738327026367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7535125017166138},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7318565845489502},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6994805335998535},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5781083703041077},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5638365149497986},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.556513249874115},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.524504542350769},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46991291642189026}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas.2012.6272177","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2012.6272177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Symposium on Circuits and Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.800000011920929,"display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W73527130","https://openalex.org/W90408420","https://openalex.org/W129275235","https://openalex.org/W2011275121","https://openalex.org/W2118137541","https://openalex.org/W2140050211","https://openalex.org/W2156652258","https://openalex.org/W2158388185","https://openalex.org/W2166473218","https://openalex.org/W2166770220","https://openalex.org/W2543456117","https://openalex.org/W3000705115","https://openalex.org/W3015646000","https://openalex.org/W6603010935","https://openalex.org/W6677723693","https://openalex.org/W6680754219","https://openalex.org/W6683372824","https://openalex.org/W6684116732","https://openalex.org/W6684625086","https://openalex.org/W7001233300"],"related_works":["https://openalex.org/W2987280934","https://openalex.org/W2093104230","https://openalex.org/W4390874210","https://openalex.org/W4384918963","https://openalex.org/W4365211920","https://openalex.org/W2128027845","https://openalex.org/W4386184937","https://openalex.org/W3014948380","https://openalex.org/W1493875009","https://openalex.org/W2751624083"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,44],"propose":[4],"a":[5],"hybrid":[6],"generative":[7],"discriminative":[8],"framework":[9,25],"for":[10],"the":[11,46,49,52],"challenging":[12],"problem":[13],"of":[14,38,51],"spam":[15],"emails":[16],"filtering":[17],"using":[18],"both":[19],"textual":[20],"and":[21,48],"visual":[22],"features.":[23],"Our":[24],"is":[26],"based":[27],"on":[28],"building":[29],"probabilistic":[30],"Support":[31],"Vector":[32],"Machines":[33],"(SVMs)":[34],"kernels":[35],"from":[36],"mixture":[37],"Langevin":[39],"distributions.":[40],"Through":[41],"empirical":[42],"experiments,":[43],"demonstrate":[45],"effectiveness":[47],"merits":[50],"proposed":[53],"learning":[54],"framework.":[55]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}