{"id":"https://openalex.org/W3009304836","doi":"https://doi.org/10.1017/s1351324920000066","title":"Unsupervised modeling anomaly detection in discussion forums posts using global vectors for text representation","display_name":"Unsupervised modeling anomaly detection in discussion forums posts using global vectors for text representation","publication_year":2020,"publication_date":"2020-03-04","ids":{"openalex":"https://openalex.org/W3009304836","doi":"https://doi.org/10.1017/s1351324920000066","mag":"3009304836"},"language":"en","primary_location":{"id":"doi:10.1017/s1351324920000066","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s1351324920000066","pdf_url":null,"source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","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/A5068140368","display_name":"Pawe\u0142 Cichosz","orcid":"https://orcid.org/0000-0002-8049-7410"},"institutions":[{"id":"https://openalex.org/I108403487","display_name":"Warsaw University of Technology","ror":"https://ror.org/00y0xnp53","country_code":"PL","type":"education","lineage":["https://openalex.org/I108403487"]},{"id":"https://openalex.org/I4210087266","display_name":"Institute of Computer Science","ror":"https://ror.org/003fvp964","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210087266","https://openalex.org/I99542240"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Pawe\u0142 Cichosz","raw_affiliation_strings":["Institute of Computer Science, Warsaw University of Technology, Warszawa, Poland E-mail:"],"raw_orcid":"https://orcid.org/0000-0002-8049-7410","affiliations":[{"raw_affiliation_string":"Institute of Computer Science, Warsaw University of Technology, Warszawa, Poland E-mail:","institution_ids":["https://openalex.org/I108403487","https://openalex.org/I4210087266"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5068140368"],"corresponding_institution_ids":["https://openalex.org/I108403487","https://openalex.org/I4210087266"],"apc_list":null,"apc_paid":null,"fwci":1.7805,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.85681205,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"26","issue":"5","first_page":"551","last_page":"578"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9980999827384949,"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"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9980999827384949,"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/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/T11644","display_name":"Spam and Phishing Detection","score":0.9955999851226807,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8057790994644165},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7356278896331787},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6751304864883423},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.606954038143158},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6044661998748779},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5957270860671997},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.5320020318031311},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49085789918899536},{"id":"https://openalex.org/keywords/bag-of-words-model","display_name":"Bag-of-words model","score":0.48065221309661865},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4525378346443176},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4163585901260376},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3883993923664093},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.2694104313850403}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8057790994644165},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7356278896331787},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6751304864883423},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.606954038143158},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6044661998748779},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5957270860671997},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.5320020318031311},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49085789918899536},{"id":"https://openalex.org/C13672336","wikidata":"https://www.wikidata.org/wiki/Q3460803","display_name":"Bag-of-words model","level":2,"score":0.48065221309661865},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4525378346443176},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4163585901260376},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3883993923664093},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.2694104313850403},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1017/s1351324920000066","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s1351324920000066","pdf_url":null,"source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":117,"referenced_works":["https://openalex.org/W40976687","https://openalex.org/W42251416","https://openalex.org/W50589830","https://openalex.org/W54330468","https://openalex.org/W273955616","https://openalex.org/W580594664","https://openalex.org/W1493454437","https://openalex.org/W1503841124","https://openalex.org/W1512098439","https://openalex.org/W1523937437","https://openalex.org/W1532325895","https://openalex.org/W1536719366","https://openalex.org/W1540550673","https://openalex.org/W1549656520","https://openalex.org/W1550206324","https://openalex.org/W1604938182","https://openalex.org/W1618905105","https://openalex.org/W1790954942","https://openalex.org/W1880262756","https://openalex.org/W1958077162","https://openalex.org/W1969082358","https://openalex.org/W1971784203","https://openalex.org/W1972222614","https://openalex.org/W1984052055","https://openalex.org/W1985059878","https://openalex.org/W1985560513","https://openalex.org/W1987971958","https://openalex.org/W1995443851","https://openalex.org/W2005542193","https://openalex.org/W2015887370","https://openalex.org/W2019014808","https://openalex.org/W2043435661","https://openalex.org/W2045199338","https://openalex.org/W2067767241","https://openalex.org/W2086830439","https://openalex.org/W2100212893","https://openalex.org/W2102589777","https://openalex.org/W2103333826","https://openalex.org/W2107772748","https://openalex.org/W2113066606","https://openalex.org/W2115627867","https://openalex.org/W2118020653","https://openalex.org/W2118587067","https://openalex.org/W2119821739","https://openalex.org/W2122646361","https://openalex.org/W2126725946","https://openalex.org/W2127218421","https://openalex.org/W2129006692","https://openalex.org/W2129066856","https://openalex.org/W2131571251","https://openalex.org/W2131744502","https://openalex.org/W2131904035","https://openalex.org/W2132870739","https://openalex.org/W2142189579","https://openalex.org/W2142472733","https://openalex.org/W2144182447","https://openalex.org/W2145819623","https://openalex.org/W2146502635","https://openalex.org/W2146838370","https://openalex.org/W2149684865","https://openalex.org/W2149706766","https://openalex.org/W2152311353","https://openalex.org/W2154322090","https://openalex.org/W2155151219","https://openalex.org/W2158698691","https://openalex.org/W2170654002","https://openalex.org/W2171975443","https://openalex.org/W2250539671","https://openalex.org/W2250662230","https://openalex.org/W2319660501","https://openalex.org/W2322087182","https://openalex.org/W2329665369","https://openalex.org/W2330820318","https://openalex.org/W2337344967","https://openalex.org/W2407757982","https://openalex.org/W2435251607","https://openalex.org/W2479526337","https://openalex.org/W2479531384","https://openalex.org/W2480068437","https://openalex.org/W2517417371","https://openalex.org/W2599331200","https://openalex.org/W2612166593","https://openalex.org/W2622411536","https://openalex.org/W2735364069","https://openalex.org/W2745980806","https://openalex.org/W2772850107","https://openalex.org/W2783314722","https://openalex.org/W2900002296","https://openalex.org/W2911964244","https://openalex.org/W2913066018","https://openalex.org/W2949547296","https://openalex.org/W2950577311","https://openalex.org/W2999729612","https://openalex.org/W3085162807","https://openalex.org/W4213009331","https://openalex.org/W4231510805","https://openalex.org/W4232545478","https://openalex.org/W4236122429","https://openalex.org/W4236137412","https://openalex.org/W4239510810","https://openalex.org/W4253794406","https://openalex.org/W4256486044","https://openalex.org/W4297797156","https://openalex.org/W6602226392","https://openalex.org/W6610017368","https://openalex.org/W6630234911","https://openalex.org/W6639619044","https://openalex.org/W6679539681","https://openalex.org/W6681135275","https://openalex.org/W6681320699","https://openalex.org/W6681435938","https://openalex.org/W6682243771","https://openalex.org/W6691431627","https://openalex.org/W6721309591","https://openalex.org/W6739262788","https://openalex.org/W6959862096","https://openalex.org/W6979954571"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W2143820878","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4300558037","https://openalex.org/W4377864969"],"abstract_inverted_index":{"Abstract":[0],"Anomaly":[1],"detection":[2,40,129,159,185,195],"can":[3],"be":[4],"seen":[5],"as":[6,61,66],"an":[7,112],"unsupervised":[8,127],"learning":[9],"task":[10],"in":[11,26,196],"which":[12,110],"a":[13,103,189],"predictive":[14],"model":[15],"created":[16],"on":[17,76,132,140],"historical":[18],"data":[19],"is":[20,94,111,149],"used":[21],"to":[22,41,53,80,142,184,193],"detect":[23],"outlying":[24],"instances":[25],"new":[27],"data.":[28,43,198],"This":[29],"work":[30],"addresses":[31],"possibly":[32,74],"promising":[33,191],"but":[34],"relatively":[35],"uncommon":[36],"application":[37],"of":[38,88,99,114,165],"anomaly":[39,128,155,194],"text":[42,67,92,169,197],"Two":[44],"English-language":[45],"and":[46,73,102,138,161,187],"one":[47],"Polish-language":[48],"Internet":[49],"discussion":[50],"forums":[51],"devoted":[52],"psychoactive":[54],"substances":[55],"received":[56],"from":[57],"home-grown":[58],"plants,":[59],"such":[60],"hashish":[62],"or":[63],"marijuana,":[64],"serve":[65],"sources":[68],"that":[69],"are":[70,122],"both":[71,123],"realistic":[72],"interesting":[75],"their":[77],"own,":[78],"due":[79],"potential":[81],"associations":[82],"with":[83,125,168,176,182],"drug-related":[84],"crime.":[85],"The":[86,146,171],"utility":[87],"two":[89,126],"different":[90],"vector":[91,135],"representations":[93],"examined:":[95],"the":[96,115,163],"simple":[97],"bag":[98],"words":[100],"representation":[101,148,178],"more":[104,152,190],"refined":[105],"Global":[106],"Vectors":[107],"(GloVe)":[108],"representation,":[109],"example":[113],"increasingly":[116],"popular":[117],"word":[118],"embedding":[119],"approach.":[120],"They":[121],"combined":[124,175],"methods,":[130],"based":[131,139],"one-class":[133,180],"support":[134],"machines":[136],"(SVM)":[137],"dissimilarity":[141,173],"k":[143],"-medoids":[144],"clusters.":[145],"GloVe":[147],"found":[150],"definitely":[151],"useful":[153],"for":[154],"detection,":[156],"permitting":[157],"better":[158],"quality":[160,186],"ameliorating":[162],"curse":[164],"dimensionality":[166],"issues":[167],"clustering.":[170],"cluster":[172],"approach":[174,192],"this":[177],"outperforms":[179],"SVM":[181],"respect":[183],"appears":[188]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-26T08:31:28.666265","created_date":"2025-10-10T00:00:00"}