{"id":"https://openalex.org/W2892343621","doi":"https://doi.org/10.1504/ijdmmm.2018.10015879","title":"Tree-based text stream clustering with application to spam mail classification","display_name":"Tree-based text stream clustering with application to spam mail classification","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2892343621","doi":"https://doi.org/10.1504/ijdmmm.2018.10015879","mag":"2892343621"},"language":"en","primary_location":{"id":"doi:10.1504/ijdmmm.2018.10015879","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijdmmm.2018.10015879","pdf_url":null,"source":{"id":"https://openalex.org/S42848612","display_name":"International Journal of Data Mining Modelling and Management","issn_l":"1759-1163","issn":["1759-1163","1759-1171"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Mining, Modelling and Management","raw_type":"journal-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/A5001323997","display_name":"Sudsanguan Ngamsuriyaroj","orcid":null},"institutions":[{"id":"https://openalex.org/I25399158","display_name":"Mahidol University","ror":"https://ror.org/01znkr924","country_code":"TH","type":"education","lineage":["https://openalex.org/I25399158"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Sudsanguan Ngamsuriyaroj","raw_affiliation_strings":["Faculty of Information and Communication Technology, Mahidol University, Salaya, Nakorn Pathom 73170, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information and Communication Technology, Mahidol University, Salaya, Nakorn Pathom 73170, Thailand","institution_ids":["https://openalex.org/I25399158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056080990","display_name":"Phimphaka Taninpong","orcid":"https://orcid.org/0000-0003-2539-0749"},"institutions":[{"id":"https://openalex.org/I25399158","display_name":"Mahidol University","ror":"https://ror.org/01znkr924","country_code":"TH","type":"education","lineage":["https://openalex.org/I25399158"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Phimphaka Taninpong","raw_affiliation_strings":["Faculty of Information and Communication Technology, Mahidol University, Salaya, Nakorn Pathom 73170, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information and Communication Technology, Mahidol University, Salaya, Nakorn Pathom 73170, Thailand","institution_ids":["https://openalex.org/I25399158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I25399158"],"apc_list":null,"apc_paid":null,"fwci":0.8054,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.81336317,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"10","issue":"4","first_page":"353","last_page":"353"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9972000122070312,"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":0.9972000122070312,"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":0.9950000047683716,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9914000034332275,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8447211980819702},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7192432880401611},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5930800437927246},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5835545063018799},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5765615105628967},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.525359570980072},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.5131000280380249},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.4827001094818115},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.453105628490448},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.4507838785648346},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.4494263827800751},{"id":"https://openalex.org/keywords/k-medians-clustering","display_name":"k-medians clustering","score":0.43992170691490173},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43275949358940125},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.4304928779602051},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17409712076187134},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.06379300355911255}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8447211980819702},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7192432880401611},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5930800437927246},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5835545063018799},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5765615105628967},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.525359570980072},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.5131000280380249},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.4827001094818115},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.453105628490448},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.4507838785648346},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.4494263827800751},{"id":"https://openalex.org/C115328559","wikidata":"https://www.wikidata.org/wiki/Q4041956","display_name":"k-medians clustering","level":5,"score":0.43992170691490173},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43275949358940125},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.4304928779602051},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17409712076187134},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.06379300355911255},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1504/ijdmmm.2018.10015879","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijdmmm.2018.10015879","pdf_url":null,"source":{"id":"https://openalex.org/S42848612","display_name":"International Journal of Data Mining Modelling and Management","issn_l":"1759-1163","issn":["1759-1163","1759-1171"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Mining, Modelling and Management","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2188840951","https://openalex.org/W2590117803","https://openalex.org/W2393816671","https://openalex.org/W2393707058","https://openalex.org/W2202413591","https://openalex.org/W2389934482","https://openalex.org/W2381835990","https://openalex.org/W2388628913","https://openalex.org/W2358133791","https://openalex.org/W2358586643"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,10,21,24,28,35,86],"new":[4,87,103],"text":[5,124],"clustering":[6,18,32,111,125],"algorithm":[7,19,33,39,112],"based":[8],"on":[9],"tree":[11,44],"structure.":[12],"The":[13],"main":[14],"idea":[15],"of":[16,56,76],"the":[17,43,54,73,92,95,102,109,118,134],"is":[20,34,89],"sub-tree":[22],"at":[23],"specific":[25],"node":[26],"represents":[27],"document":[29,65,88],"cluster.":[30],"Our":[31],"single":[36],"pass":[37],"scanning":[38],"which":[40],"traverses":[41],"down":[42],"to":[45,52,63,71,100,113],"search":[46],"for":[47],"all":[48],"clusters":[49,66,96],"without":[50],"having":[51,67],"predefine":[53],"number":[55,75],"clusters.":[57,77],"Thus,":[58],"it":[59],"fits":[60],"our":[61],"objectives":[62],"produce":[64],"high":[68],"cohesion,":[69],"and":[70,94,117,131,139],"keep":[72],"minimum":[74],"Moreover,":[78],"an":[79],"incremental":[80],"learning":[81],"process":[82],"will":[83,97],"perform":[84],"after":[85],"inserted":[90],"into":[91],"tree,":[93],"be":[98],"rebuilt":[99],"accommodate":[101],"information.":[104],"In":[105],"addition,":[106],"we":[107],"applied":[108],"proposed":[110],"spam":[114,126],"mail":[115],"classification":[116],"experimental":[119],"results":[120],"show":[121],"that":[122],"tree-based":[123],"filter":[127],"gives":[128],"higher":[129],"accuracy":[130],"specificity":[132],"than":[133],"cobweb":[135],"clustering,":[136],"na\u00efve":[137],"Bayes":[138],"KNN.":[140]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
