{"id":"https://openalex.org/W1652282666","doi":"https://doi.org/10.1109/icacci.2015.7275862","title":"Consensus based ensemble model for spam detection","display_name":"Consensus based ensemble model for spam detection","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W1652282666","doi":"https://doi.org/10.1109/icacci.2015.7275862","mag":"1652282666"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2015.7275862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2015.7275862","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5008012631","display_name":"Paritosh Pantola","orcid":null},"institutions":[{"id":"https://openalex.org/I162030827","display_name":"Thapar Institute of Engineering & Technology","ror":"https://ror.org/00wdq3744","country_code":"IN","type":"education","lineage":["https://openalex.org/I162030827"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Paritosh Pantola","raw_affiliation_strings":["Computer Science and Engineering Department, Thapar University, Patiala, Punjab, India","Computer Science and Engineering Department, Thapar University, Patiala, Punjab India"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, Thapar University, Patiala, Punjab, India","institution_ids":["https://openalex.org/I162030827"]},{"raw_affiliation_string":"Computer Science and Engineering Department, Thapar University, Patiala, Punjab India","institution_ids":["https://openalex.org/I162030827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101417162","display_name":"Anju Bala","orcid":"https://orcid.org/0000-0001-9786-4347"},"institutions":[{"id":"https://openalex.org/I162030827","display_name":"Thapar Institute of Engineering & Technology","ror":"https://ror.org/00wdq3744","country_code":"IN","type":"education","lineage":["https://openalex.org/I162030827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anju Bala","raw_affiliation_strings":["Computer Science and Engineering Department, Thapar University, Patiala, Punjab, India","Computer Science and Engineering Department, Thapar University, Patiala, Punjab India"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, Thapar University, Patiala, Punjab, India","institution_ids":["https://openalex.org/I162030827"]},{"raw_affiliation_string":"Computer Science and Engineering Department, Thapar University, Patiala, Punjab India","institution_ids":["https://openalex.org/I162030827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071186894","display_name":"Prashant Singh Rana","orcid":"https://orcid.org/0000-0002-0142-7925"},"institutions":[{"id":"https://openalex.org/I162030827","display_name":"Thapar Institute of Engineering & Technology","ror":"https://ror.org/00wdq3744","country_code":"IN","type":"education","lineage":["https://openalex.org/I162030827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Prashant Singh Rana","raw_affiliation_strings":["Computer Science and Engineering Department, Thapar University, Patiala, Punjab, India","Computer Science and Engineering Department, Thapar University, Patiala, Punjab India"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, Thapar University, Patiala, Punjab, India","institution_ids":["https://openalex.org/I162030827"]},{"raw_affiliation_string":"Computer Science and Engineering Department, Thapar University, Patiala, Punjab India","institution_ids":["https://openalex.org/I162030827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008012631"],"corresponding_institution_ids":["https://openalex.org/I162030827"],"apc_list":null,"apc_paid":null,"fwci":1.3354,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.85704585,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"89","issue":null,"first_page":"1724","last_page":"1727"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.998199999332428,"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"}},"topics":[{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.998199999332428,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","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"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/robustness","display_name":"Robustness (evolution)","score":0.7270708084106445},{"id":"https://openalex.org/keywords/confusion-matrix","display_name":"Confusion matrix","score":0.7195466756820679},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.709671139717102},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6515456438064575},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6227248907089233},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5955554842948914},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.5883519649505615},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5546655058860779},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.5501950979232788},{"id":"https://openalex.org/keywords/confusion","display_name":"Confusion","score":0.5493516325950623},{"id":"https://openalex.org/keywords/multiple-models","display_name":"Multiple Models","score":0.45524781942367554},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4244823455810547},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.42313581705093384},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.4182666540145874},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41448381543159485},{"id":"https://openalex.org/keywords/kappa","display_name":"Kappa","score":0.41113096475601196},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36721402406692505},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14897531270980835},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0710783302783966}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7270708084106445},{"id":"https://openalex.org/C138602881","wikidata":"https://www.wikidata.org/wiki/Q2709591","display_name":"Confusion matrix","level":2,"score":0.7195466756820679},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.709671139717102},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6515456438064575},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6227248907089233},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5955554842948914},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.5883519649505615},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5546655058860779},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.5501950979232788},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.5493516325950623},{"id":"https://openalex.org/C2779714256","wikidata":"https://www.wikidata.org/wiki/Q25305062","display_name":"Multiple Models","level":2,"score":0.45524781942367554},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4244823455810547},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.42313581705093384},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.4182666540145874},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41448381543159485},{"id":"https://openalex.org/C2778724333","wikidata":"https://www.wikidata.org/wiki/Q14401","display_name":"Kappa","level":2,"score":0.41113096475601196},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36721402406692505},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14897531270980835},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0710783302783966},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","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/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icacci.2015.7275862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2015.7275862","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W128984794","https://openalex.org/W273955616","https://openalex.org/W1598333443","https://openalex.org/W1976193075","https://openalex.org/W1981039744","https://openalex.org/W1988790447","https://openalex.org/W2056392803","https://openalex.org/W2102201073","https://openalex.org/W2125055259","https://openalex.org/W2140586694","https://openalex.org/W2143908786","https://openalex.org/W2149706766","https://openalex.org/W2161062919","https://openalex.org/W2164777277","https://openalex.org/W2318181068","https://openalex.org/W2330820318","https://openalex.org/W2597456101","https://openalex.org/W3085162807","https://openalex.org/W3124533140","https://openalex.org/W4233372644","https://openalex.org/W4236137412","https://openalex.org/W6610017368","https://openalex.org/W6636422352","https://openalex.org/W6678449394","https://openalex.org/W6789280862"],"related_works":["https://openalex.org/W2794896638","https://openalex.org/W2891633941","https://openalex.org/W3202800081","https://openalex.org/W3101614107","https://openalex.org/W4390971112","https://openalex.org/W3036530763","https://openalex.org/W4383368890","https://openalex.org/W1909207154","https://openalex.org/W2201958145","https://openalex.org/W3176003670"],"abstract_inverted_index":{"In":[0,54],"machine":[1,60],"learning,":[2],"ensemble":[3,27],"model":[4,23,28,48],"is":[5],"combining":[6],"two":[7],"or":[8],"more":[9],"models":[10],"for":[11,50,63],"obtaining":[12],"the":[13,46,64],"better":[14],"prediction,":[15],"accuracy":[16],"and":[17,78],"robustness":[18],"as":[19],"compared":[20],"to":[21,32,44,88],"individual":[22],"separately.":[24],"Before":[25],"getting":[26],"first":[29],"we":[30,42,57,83],"have":[31,43],"assign":[33],"our":[34,51,89],"training":[35],"dataset":[36],"into":[37],"different":[38],"models,":[39],"after":[40],"that":[41,82],"select":[45],"best":[47,90],"suited":[49],"data":[52,65],"sets.":[53],"this":[55],"work":[56],"explored":[58],"six":[59],"learning":[61],"parameter":[62],"set":[66],"i.e.":[67],"Accuracy,":[68],"Receiver":[69],"operating":[70],"characteristics":[71],"(ROC)":[72],"curve,":[73],"Confusion":[74],"matrix,":[75],"Sensitivity,":[76],"Specificity":[77],"Kappa":[79],"value.":[80],"After":[81],"implemented":[84],"k":[85],"fold":[86],"validation":[87],"five":[91],"models.":[92]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}