{"id":"https://openalex.org/W3149684950","doi":"https://doi.org/10.1109/ccwc51732.2021.9375922","title":"Semi-Automatic Reliable Explanations for Prediction in Graphs","display_name":"Semi-Automatic Reliable Explanations for Prediction in Graphs","publication_year":2021,"publication_date":"2021-01-27","ids":{"openalex":"https://openalex.org/W3149684950","doi":"https://doi.org/10.1109/ccwc51732.2021.9375922","mag":"3149684950"},"language":"en","primary_location":{"id":"doi:10.1109/ccwc51732.2021.9375922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc51732.2021.9375922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC)","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/A5046862839","display_name":"Masaru Todoriki","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Masaru Todoriki","raw_affiliation_strings":["Artificial Intelligence Laboratory, Fujitsu Laboratories Ltd., Kanagawa, Japan"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Laboratory, Fujitsu Laboratories Ltd., Kanagawa, Japan","institution_ids":["https://openalex.org/I2252096349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004420965","display_name":"Masafumi Shingu","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masafumi Shingu","raw_affiliation_strings":["Artificial Intelligence Laboratory, Fujitsu Laboratories Ltd., Kanagawa, Japan"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Laboratory, Fujitsu Laboratories Ltd., Kanagawa, Japan","institution_ids":["https://openalex.org/I2252096349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009887814","display_name":"Shotaro Yano","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shotaro Yano","raw_affiliation_strings":["Fujitsu Kyushu Network Technologies Limited, Fukuoka, Japan"],"affiliations":[{"raw_affiliation_string":"Fujitsu Kyushu Network Technologies Limited, Fukuoka, Japan","institution_ids":["https://openalex.org/I2252096349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075775591","display_name":"Arseny Tolmachev","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Arseny Tolmachev","raw_affiliation_strings":["Artificial Intelligence Laboratory, Fujitsu Laboratories Ltd., Kanagawa, Japan"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Laboratory, Fujitsu Laboratories Ltd., Kanagawa, Japan","institution_ids":["https://openalex.org/I2252096349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011044231","display_name":"Tao Komikado","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tao Komikado","raw_affiliation_strings":["Artificial Intelligence Laboratory, Fujitsu Laboratories Ltd., Kanagawa, Japan"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Laboratory, Fujitsu Laboratories Ltd., Kanagawa, Japan","institution_ids":["https://openalex.org/I2252096349"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066599523","display_name":"Koji Maruhashi","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koji Maruhashi","raw_affiliation_strings":["Artificial Intelligence Laboratory, Fujitsu Laboratories Ltd., Kanagawa, Japan"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Laboratory, Fujitsu Laboratories Ltd., Kanagawa, Japan","institution_ids":["https://openalex.org/I2252096349"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5046862839"],"corresponding_institution_ids":["https://openalex.org/I2252096349"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51469012,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"286","issue":null,"first_page":"0311","last_page":"0320"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9995999932289124,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9995999932289124,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9965000152587891,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9944999814033508,"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":0.6703478097915649},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3460760712623596}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6703478097915649},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3460760712623596}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccwc51732.2021.9375922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc51732.2021.9375922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1787224781","https://openalex.org/W2008620264","https://openalex.org/W2008857988","https://openalex.org/W2116341502","https://openalex.org/W2240067561","https://openalex.org/W2282821441","https://openalex.org/W2516809705","https://openalex.org/W2616247523","https://openalex.org/W2772984056","https://openalex.org/W2788403449","https://openalex.org/W2891503716","https://openalex.org/W2905224888","https://openalex.org/W2907492528","https://openalex.org/W2925177113","https://openalex.org/W2955782190","https://openalex.org/W2958089299","https://openalex.org/W2962851944","https://openalex.org/W2962862931","https://openalex.org/W2963095307","https://openalex.org/W2963847595","https://openalex.org/W2964015378","https://openalex.org/W2964303497","https://openalex.org/W2964311892","https://openalex.org/W2972317931","https://openalex.org/W2981731882","https://openalex.org/W2988571238","https://openalex.org/W3000716014","https://openalex.org/W3004315562","https://openalex.org/W3006141194","https://openalex.org/W3006236094","https://openalex.org/W3011667710","https://openalex.org/W3037881545","https://openalex.org/W3101981467","https://openalex.org/W3102564565","https://openalex.org/W3103523530","https://openalex.org/W3152893301","https://openalex.org/W4210257598","https://openalex.org/W4287866758","https://openalex.org/W4288313203","https://openalex.org/W6652609139","https://openalex.org/W6685133223","https://openalex.org/W6726873649","https://openalex.org/W6737947904","https://openalex.org/W6746228475","https://openalex.org/W6748426178","https://openalex.org/W6773564791","https://openalex.org/W6785645550","https://openalex.org/W6891886391"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032","https://openalex.org/W2382290278"],"abstract_inverted_index":{"We":[0,150,263,282],"discuss":[1],"reliability":[2],"for":[3,6,56,156,162,210,255,292],"local":[4,42,120,153],"explanations":[5,190,257],"prediction":[7,216,297],"in":[8,25,77,201,224,288],"graphs.":[9],"Meaningfully":[10],"explaining":[11],"predictions":[12],"of":[13,60,80,91,111,137,143,145,170,196,229,237,259],"machine":[14],"learning":[15],"models":[16,298],"is":[17,33,71,95,114,232,250,343],"an":[18],"open":[19],"and":[20,51,64,103,109,140,161,218,296],"important":[21,253],"research":[22],"question":[23],"particularly":[24],"relation":[26],"to":[27,36,83,106,117,123,131,187,222,269,331],"human":[28,277],"judgement.":[29],"Objectively":[30],"evaluating":[31],"explanation":[32,43,121,154,203,274,340],"strongly":[34],"required":[35],"make":[37],"Artificial":[38],"Intelligence":[39],"trusted.":[40],"Model-agnostic":[41],"methods":[44,122],"such":[45,119,133,299],"as":[46,134,300,345],"LIME":[47,160],"have":[48],"recently":[49],"emerged":[50],"are":[52,128,205],"being":[53],"widely":[54],"used":[55,58],"commonly":[57],"types":[59],"data:":[61],"tables,":[62],"texts,":[63],"images.":[65],"A":[66],"locally":[67,318],"linear":[68,319],"regression":[69,320],"model":[70,321],"constructed":[72],"using":[73,279],"perturbed":[74,93,171,177,192,211,239],"data":[75,94,125,172,178,219,240],"generated":[76],"the":[78,81,89,101,135,138,141,146,168,197,202,227,235,238,247,251,260,317,329,337],"vicinity":[79],"instance":[82,248],"be":[84],"explained":[85],"with":[86,275,310,336],"LIME.":[87],"However,":[88],"creation":[90],"adequate":[92],"not":[96],"necessarily":[97],"easy":[98],"depending":[99],"on":[100],"task":[102],"dataset":[104],"leading":[105],"less":[107],"explainability":[108,334],"instability":[110],"explanations.":[112],"It":[113],"more":[115],"problematic":[116],"apply":[118],"graph":[124,293,301,311,339],"because":[126],"there":[127,184],"difficulties":[129],"unique":[130],"graphs":[132,157],"complexity":[136],"structure":[139],"variety":[142],"definitions":[144],"distance":[147,213],"among":[148],"them.":[149],"propose":[151,265],"a":[152,185,207,243,266,272,285,346],"method":[155,209,268,291,341],"originated":[158],"from":[159],"fundamental":[163],"synthetic":[164],"datasets":[165],"experimentally":[166],"investigate":[167],"characteristics":[169],"concerning":[173],"explainability,":[174],"e.g.,":[175],"\u201cwhat":[176],"can":[179,322],"increase":[180],"explainability?\u201d":[181],"or":[182,305],"\u201cis":[183],"criterion":[186],"determine":[188,271],"reliable":[189,273],"regarding":[191],"data?\u201d.":[193],"The":[194,313],"effect":[195,228],"following":[198],"various":[199],"factors":[200,231],"process":[204],"investigated:":[206],"generation":[208],"data,":[212],"function,":[214],"dataset,":[215],"model,":[217],"augmentation":[220],"due":[221],"noise":[223],"training.":[225],"Although":[226],"these":[230],"quite":[233],"complex,":[234],"ratio":[236],"that":[241,316],"has":[242,249],"different":[244],"class":[245],"than":[246,335],"most":[252],"index":[254],"higher":[256],"independently":[258],"complex":[261],"effect.":[262],"also":[264,283],"practical":[267],"semi-automatically":[270],"minimum":[276],"support":[278,306],"this":[280],"index.":[281],"evaluate":[284],"model-agnostic":[286],"manner":[287],"our":[289],"proposed":[290],"classification":[294],"tasks":[295],"convolutional":[302],"networks":[303],"(GCNs)":[304],"vector":[307],"machines":[308],"(SVM)":[309],"kernels.":[312],"results":[314],"indicate":[315],"work":[323],"well":[324],"under":[325],"specific":[326],"situations.":[327],"Moreover,":[328],"possibility":[330],"obtain":[332],"better":[333],"state-of-the-art":[338],"GNNExplainer":[342],"shown":[344],"reference.":[347]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}