{"id":"https://openalex.org/W4386363071","doi":"https://doi.org/10.1109/access.2023.3311146","title":"TransSentLog: Interpretable Anomaly Detection Using Transformer and Sentiment Analysis on Individual Log Event","display_name":"TransSentLog: Interpretable Anomaly Detection Using Transformer and Sentiment Analysis on Individual Log Event","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386363071","doi":"https://doi.org/10.1109/access.2023.3311146"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3311146","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3311146","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10237208.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10237208.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085823378","display_name":"Tuan-Anh Pham","orcid":"https://orcid.org/0000-0001-5049-529X"},"institutions":[{"id":"https://openalex.org/I2799865230","display_name":"Green Cross (South Korea)","ror":"https://ror.org/01k0xxh86","country_code":"KR","type":"company","lineage":["https://openalex.org/I2799865230"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Tuan-Anh Pham","raw_affiliation_strings":["Department of AI Laboratory, MOADATA, Global Convergence Center, Seongnam-si, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of AI Laboratory, MOADATA, Global Convergence Center, Seongnam-si, South Korea","institution_ids":["https://openalex.org/I2799865230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101884291","display_name":"Jonghoon Lee","orcid":"https://orcid.org/0000-0002-7059-3126"},"institutions":[{"id":"https://openalex.org/I2799865230","display_name":"Green Cross (South Korea)","ror":"https://ror.org/01k0xxh86","country_code":"KR","type":"company","lineage":["https://openalex.org/I2799865230"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jong-Hoon Lee","raw_affiliation_strings":["Department of AI Laboratory, MOADATA, Global Convergence Center, Seongnam-si, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of AI Laboratory, MOADATA, Global Convergence Center, Seongnam-si, South Korea","institution_ids":["https://openalex.org/I2799865230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5085823378"],"corresponding_institution_ids":["https://openalex.org/I2799865230"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.3963,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.89470013,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"11","issue":null,"first_page":"96272","last_page":"96282"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9998999834060669,"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/T12127","display_name":"Software System Performance and Reliability","score":0.9998999834060669,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9991999864578247,"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":0.996999979019165,"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":0.7871941924095154},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6867886781692505},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.6190986633300781},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5715975165367126},{"id":"https://openalex.org/keywords/polarity","display_name":"Polarity (international relations)","score":0.5277971625328064},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5108823180198669},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5086928009986877},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.47581034898757935},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4238927960395813},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3979359269142151},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3628206253051758}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7871941924095154},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6867886781692505},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.6190986633300781},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5715975165367126},{"id":"https://openalex.org/C2777361361","wikidata":"https://www.wikidata.org/wiki/Q1112585","display_name":"Polarity (international relations)","level":3,"score":0.5277971625328064},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5108823180198669},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5086928009986877},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.47581034898757935},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4238927960395813},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3979359269142151},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3628206253051758},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C1491633281","wikidata":"https://www.wikidata.org/wiki/Q7868","display_name":"Cell","level":2,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3311146","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3311146","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10237208.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4831f4931d3f42139f740c4954394ac5","is_oa":true,"landing_page_url":"https://doaj.org/article/4831f4931d3f42139f740c4954394ac5","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 96272-96282 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3311146","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3311146","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10237208.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386363071.pdf","grobid_xml":"https://content.openalex.org/works/W4386363071.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W995372445","https://openalex.org/W1591261915","https://openalex.org/W2022887050","https://openalex.org/W2076342816","https://openalex.org/W2122646361","https://openalex.org/W2157331557","https://openalex.org/W2168681026","https://openalex.org/W2250539671","https://openalex.org/W2401686019","https://openalex.org/W2594633041","https://openalex.org/W2767094836","https://openalex.org/W2903655746","https://openalex.org/W2908510526","https://openalex.org/W2947189214","https://openalex.org/W2963174729","https://openalex.org/W2963999143","https://openalex.org/W2965838158","https://openalex.org/W2968917279","https://openalex.org/W3013748100","https://openalex.org/W3099104041","https://openalex.org/W3129163867","https://openalex.org/W3185152627","https://openalex.org/W3194035167","https://openalex.org/W4385245566","https://openalex.org/W6712994927","https://openalex.org/W6734194636","https://openalex.org/W6739901393","https://openalex.org/W6754450847","https://openalex.org/W6757053875","https://openalex.org/W6757817989","https://openalex.org/W6767164110"],"related_works":["https://openalex.org/W2548633793","https://openalex.org/W3089396779","https://openalex.org/W2354902965","https://openalex.org/W2596247554","https://openalex.org/W4301373556","https://openalex.org/W2941935829","https://openalex.org/W3013279174","https://openalex.org/W4317653575","https://openalex.org/W3132372214","https://openalex.org/W1984947604"],"abstract_inverted_index":{"Event":[0],"logs":[1,14,40],"play":[2],"a":[3,20,34,93],"crucial":[4],"role":[5],"in":[6,64],"monitoring":[7],"the":[8,69,85,97,112,130],"status":[9],"of":[10,88,96,132,139],"IT":[11],"systems.":[12],"These":[13],"contain":[15],"text":[16],"that":[17,107,125],"describes":[18],"how":[19],"system":[21,35,120],"operates":[22],"using":[23],"natural":[24],"language,":[25],"which":[26],"can":[27,56],"be":[28,57],"associated":[29],"with":[30],"sentiment":[31,55,82,86],"polarity.":[32],"When":[33],"is":[36],"functioning":[37],"correctly,":[38],"event":[39,89],"generally":[41],"convey":[42],"positive":[43],"sentiment.":[44],"However,":[45],"if":[46],"unexpected":[47],"behaviors":[48],"like":[49],"errors":[50],"or":[51],"failures":[52],"occur,":[53],"negative":[54],"detected.":[58],"In":[59],"order":[60],"to":[61],"identify":[62],"anomalies":[63],"individual":[65],"log":[66,72,121],"messages":[67],"without":[68],"need":[70],"for":[71],"parsing,":[73],"we":[74,100,123],"propose":[75],"TranSentLog.":[76],"This":[77],"method":[78,106,128],"combines":[79],"Transformer":[80],"and":[81,135,144],"analysis,":[83],"leveraging":[84],"polarity":[87],"logs.":[90],"To":[91],"gain":[92],"better":[94],"understanding":[95],"model":[98,113],"predictions,":[99],"employ":[101],"Integrated":[102],"Gradients,":[103],"an":[104],"attribution":[105],"extracts":[108],"important":[109],"features":[110],"from":[111],"inputs.":[114],"Through":[115],"extensive":[116],"experimentation":[117],"on":[118,141,146],"public":[119],"datasets,":[122],"demonstrate":[124],"our":[126],"proposed":[127],"overcomes":[129],"limitations":[131],"existing":[133],"approaches":[134],"achieves":[136],"F1":[137],"scores":[138],"99.73%":[140],"trained":[142],"datasets":[143],"94.99%":[145],"untrained":[147],"datasets.":[148]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}