{"id":"https://openalex.org/W4392980788","doi":"https://doi.org/10.1109/icaiic60209.2024.10463267","title":"Signed Graph Laplacian for Semi-Supervised Anomaly Detection","display_name":"Signed Graph Laplacian for Semi-Supervised Anomaly Detection","publication_year":2024,"publication_date":"2024-02-19","ids":{"openalex":"https://openalex.org/W4392980788","doi":"https://doi.org/10.1109/icaiic60209.2024.10463267"},"language":"en","primary_location":{"id":"doi:10.1109/icaiic60209.2024.10463267","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icaiic60209.2024.10463267","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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/A5103075264","display_name":"Jihong Bae","orcid":"https://orcid.org/0009-0008-9351-6474"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jihong Bae","raw_affiliation_strings":["Sungkyunkwan University,Department of Mathematics,Republic of Korea","Department of Mathematics, Sungkyunkwan University, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0008-9351-6474","affiliations":[{"raw_affiliation_string":"Sungkyunkwan University,Department of Mathematics,Republic of Korea","institution_ids":["https://openalex.org/I848706"]},{"raw_affiliation_string":"Department of Mathematics, Sungkyunkwan University, Republic of Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017145325","display_name":"Hyeongcheol Park","orcid":"https://orcid.org/0000-0003-4507-2991"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hyeongcheol Park","raw_affiliation_strings":["S- Traffic Co., Ltd.,MaaS Division,Republic of Korea","MaaS Division, S- Traffic Co., Ltd., Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0003-4507-2991","affiliations":[{"raw_affiliation_string":"S- Traffic Co., Ltd.,MaaS Division,Republic of Korea","institution_ids":[]},{"raw_affiliation_string":"MaaS Division, S- Traffic Co., Ltd., Republic of Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001773388","display_name":"M.J. Chung","orcid":"https://orcid.org/0009-0008-0904-3134"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Minsoo Chung","raw_affiliation_strings":["S- Traffic Co., Ltd.,MaaS Division,Republic of Korea","MaaS Division, S- Traffic Co., Ltd., Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0008-0904-3134","affiliations":[{"raw_affiliation_string":"S- Traffic Co., Ltd.,MaaS Division,Republic of Korea","institution_ids":[]},{"raw_affiliation_string":"MaaS Division, S- Traffic Co., Ltd., Republic of Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036705459","display_name":"Muhammad Toaha Raza Khan","orcid":"https://orcid.org/0000-0003-2180-0923"},"institutions":[{"id":"https://openalex.org/I69050122","display_name":"Near East University","ror":"https://ror.org/02x8svs93","country_code":"CY","type":"education","lineage":["https://openalex.org/I69050122"]}],"countries":["CY"],"is_corresponding":false,"raw_author_name":"Muhammad Toaha Raza Khan","raw_affiliation_strings":["Middle East Technical University,Computer Engineering Department,Turkish Republic of North Cyprus","Computer Engineering Department, Middle East Technical University, Turkish Republic of North Cyprus"],"raw_orcid":"https://orcid.org/0000-0003-2180-0923","affiliations":[{"raw_affiliation_string":"Middle East Technical University,Computer Engineering Department,Turkish Republic of North Cyprus","institution_ids":["https://openalex.org/I69050122"]},{"raw_affiliation_string":"Computer Engineering Department, Middle East Technical University, Turkish Republic of North Cyprus","institution_ids":["https://openalex.org/I69050122"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103180097","display_name":"Kyungchul Lee","orcid":"https://orcid.org/0009-0001-7468-9862"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kyungchul Lee","raw_affiliation_strings":["S- Traffic Co., Ltd.,MaaS Division,Republic of Korea","MaaS Division, S- Traffic Co., Ltd., Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0001-7468-9862","affiliations":[{"raw_affiliation_string":"S- Traffic Co., Ltd.,MaaS Division,Republic of Korea","institution_ids":[]},{"raw_affiliation_string":"MaaS Division, S- Traffic Co., Ltd., Republic of Korea","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103075264"],"corresponding_institution_ids":["https://openalex.org/I848706"],"apc_list":null,"apc_paid":null,"fwci":0.3311,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61109194,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"70","issue":null,"first_page":"102","last_page":"107"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9940999746322632,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9940999746322632,"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":0.9772999882698059,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.925599992275238,"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/anomaly-detection","display_name":"Anomaly detection","score":0.6580699682235718},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5686043500900269},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4775156080722809},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46064168214797974},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4242566227912903},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.22339162230491638}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6580699682235718},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5686043500900269},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4775156080722809},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46064168214797974},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4242566227912903},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.22339162230491638}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaiic60209.2024.10463267","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icaiic60209.2024.10463267","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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":31,"referenced_works":["https://openalex.org/W108936587","https://openalex.org/W1583837637","https://openalex.org/W1967509640","https://openalex.org/W2032280284","https://openalex.org/W2101210369","https://openalex.org/W2107699930","https://openalex.org/W2132914434","https://openalex.org/W2165489143","https://openalex.org/W2165874743","https://openalex.org/W2777948323","https://openalex.org/W2895281799","https://openalex.org/W2902758299","https://openalex.org/W2910068345","https://openalex.org/W2985406498","https://openalex.org/W3040266635","https://openalex.org/W3110791097","https://openalex.org/W3135550350","https://openalex.org/W3161198055","https://openalex.org/W3174989191","https://openalex.org/W3202018618","https://openalex.org/W4224232069","https://openalex.org/W4231620004","https://openalex.org/W4303183714","https://openalex.org/W4367294119","https://openalex.org/W4376456641","https://openalex.org/W6684578312","https://openalex.org/W6735050833","https://openalex.org/W6773244793","https://openalex.org/W6809455566","https://openalex.org/W6810526858","https://openalex.org/W6844196763"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,24,110,139,216,238],"is":[2,16,34,72,91,118,127,133,174,197],"a":[3,54,95,134,147,179,225],"cutting-edge":[4],"technology":[5],"in":[6,42,79,170],"the":[7,20,67,158,211],"fields":[8],"of":[9,22,57,69,87,98,108,181,213,227],"healthcare":[10],"and":[11,39,48,115,153,178,230],"machine":[12],"failure":[13],"detection.":[14,81],"It":[15],"well":[17],"known":[18],"that":[19,149,204,232],"performance":[21,212],"anomaly":[23,80,88,109,215,237],"can":[25,60,75,209],"be":[26],"improved":[27],"with":[28],"more":[29],"labeled":[30,50,58,116,176],"data.":[31,51,100,183],"However,":[32,66,123],"it":[33,90,233],"common":[35],"to":[36,62,77,93,104,119,136,156,166],"predict":[37],"anomalous":[38],"normal":[40],"data":[41,47,59,71,114,117,130,177],"where":[43,172],"are":[44],"large":[45,55,96],"unlabeled":[46,99,113,182],"small":[49],"Generally,":[52],"using":[53,111,205],"amount":[56,97],"lead":[61,76],"high":[63,84,106,138,168],"accuracy":[64,169],"prediction.":[65],"cost":[68],"labeling":[70],"expensive,":[73],"which":[74,196],"challenges":[78],"To":[82,141],"achieve":[83,105],"prediction":[85],"rate":[86],"detection,":[89],"required":[92],"utilize":[94],"The":[101,160],"only":[102],"way":[103],"rates":[107],"both":[112],"use":[120],"semi-supervised":[121,125,154,236],"learning.":[122],"if":[124],"learning":[126,155],"used":[128],"without":[129],"preprocessing,":[131],"there":[132,173],"limitation":[135],"obtain":[137],"rates.":[140],"perform":[142],"effectively":[143],"preprocess,":[144],"we":[145,219],"propose":[146],"scheme":[148,162,188,223],"leverages":[150],"graph":[151,164,194,200,207],"theory":[152],"address":[157],"limitation.":[159],"proposed":[161,222],"uses":[163],"Laplacian":[165,208],"get":[167],"situations":[171],"little":[175],"lot":[180],"We":[184,202],"further":[185],"extend":[186],"our":[187,214,221],"by":[189],"considering":[190],"friendly-antagonistic":[191],"interactions":[192],"into":[193],"Laplacian,":[195],"called":[198],"signed":[199,206],"Laplacian.":[201],"show":[203,231],"improve":[210],"scheme.":[217],"Furthermore,":[218],"evaluate":[220],"on":[224],"variety":[226],"validated":[228],"datasets":[229],"outperforms":[234],"state-of-the-art":[235],"methods.":[239]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}
