{"id":"https://openalex.org/W7126050215","doi":"https://doi.org/10.1145/3778265.3778273","title":"A Deconfounded Model for Fault Diagnosis and Retrieval of Fault Texts","display_name":"A Deconfounded Model for Fault Diagnosis and Retrieval of Fault Texts","publication_year":2025,"publication_date":"2025-10-29","ids":{"openalex":"https://openalex.org/W7126050215","doi":"https://doi.org/10.1145/3778265.3778273"},"language":null,"primary_location":{"id":"doi:10.1145/3778265.3778273","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3778265.3778273","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 7th International Conference on Big-data Service and Intelligent Computation","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3778265.3778273","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104146621","display_name":"Boru Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210105312","display_name":"Shanghai Power Equipment Research Institute","ror":"https://ror.org/01pw44479","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210105312"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Boru Lin","raw_affiliation_strings":["Shanghai Aerospace Equipments Manufacture Co.,Ltd., Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0005-8251-0577","affiliations":[{"raw_affiliation_string":"Shanghai Aerospace Equipments Manufacture Co.,Ltd., Shanghai, China","institution_ids":["https://openalex.org/I4210105312"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhiyuan Chen","orcid":"https://orcid.org/0009-0005-2300-6637"},"institutions":[{"id":"https://openalex.org/I4210105312","display_name":"Shanghai Power Equipment Research Institute","ror":"https://ror.org/01pw44479","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210105312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Chen","raw_affiliation_strings":["Shanghai Aerospace Equipments Manufacture Co.,Ltd., Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0005-2300-6637","affiliations":[{"raw_affiliation_string":"Shanghai Aerospace Equipments Manufacture Co.,Ltd., Shanghai, China","institution_ids":["https://openalex.org/I4210105312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124220225","display_name":"Shichen Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shichen Yang","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0003-5085-8670","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124164441","display_name":"Zizhao Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zizhao Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0003-2196-5944","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":null,"display_name":"Honglei Peng","orcid":"https://orcid.org/0009-0002-2289-4095"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honglei Peng","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0002-2289-4095","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5104146621"],"corresponding_institution_ids":["https://openalex.org/I4210105312"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.66156553,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"51","last_page":"62"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.48579999804496765,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.48579999804496765,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.052400000393390656,"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/T12127","display_name":"Software System Performance and Reliability","score":0.04610000178217888,"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/robustness","display_name":"Robustness (evolution)","score":0.6732000112533569},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.6391000151634216},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5449000000953674},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5067999958992004},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.4438000023365021},{"id":"https://openalex.org/keywords/fault-model","display_name":"Fault model","score":0.4259999990463257},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.41019999980926514}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6877999901771545},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6732000112533569},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.6391000151634216},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5703999996185303},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5449000000953674},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5067999958992004},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45730000734329224},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4438000023365021},{"id":"https://openalex.org/C167391956","wikidata":"https://www.wikidata.org/wiki/Q1401211","display_name":"Fault model","level":3,"score":0.4259999990463257},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.41019999980926514},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.40549999475479126},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37310001254081726},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.3481999933719635},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3361999988555908},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.33180001378059387},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32850000262260437},{"id":"https://openalex.org/C126953365","wikidata":"https://www.wikidata.org/wiki/Q5438152","display_name":"Fault coverage","level":3,"score":0.30820000171661377},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.2750000059604645},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.2637999951839447},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3778265.3778273","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3778265.3778273","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 7th International Conference on Big-data Service and Intelligent Computation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3778265.3778273","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3778265.3778273","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 7th International Conference on Big-data Service and Intelligent Computation","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1527959024","https://openalex.org/W1550784029","https://openalex.org/W1968987968","https://openalex.org/W1980867644","https://openalex.org/W2061815108","https://openalex.org/W2134332934","https://openalex.org/W2255466643","https://openalex.org/W2560730294","https://openalex.org/W2588941434","https://openalex.org/W2962735233","https://openalex.org/W2963349562","https://openalex.org/W2965180676","https://openalex.org/W2997668629","https://openalex.org/W3087070736","https://openalex.org/W3090586341","https://openalex.org/W3112482057","https://openalex.org/W3152619510","https://openalex.org/W3210997809","https://openalex.org/W4214519690","https://openalex.org/W4288735114","https://openalex.org/W4390563409","https://openalex.org/W4391204713","https://openalex.org/W4391965972","https://openalex.org/W4392872559","https://openalex.org/W4399369809","https://openalex.org/W4400438563","https://openalex.org/W4401046320","https://openalex.org/W4404211716","https://openalex.org/W4404893524"],"related_works":[],"abstract_inverted_index":{"During":[0],"the":[1,61,77,131],"maintenance":[2,69],"of":[3,64,133],"industrial":[4],"products,":[5],"fault":[6,14,18,23],"analysis":[7],"and":[8,22,30,92,98,107,129],"repair":[9],"are":[10,74,110],"primarily":[11],"guided":[12],"by":[13,38],"records,":[15],"which":[16],"document":[17],"mechanisms,":[19],"affected":[20],"components,":[21],"symptoms.":[24],"Existing":[25],"methods":[26],"for":[27,96],"case":[28,135],"retrieval":[29],"feature":[31,100,105],"extraction":[32,63],"frequently":[33],"suffer":[34],"from":[35,67,90],"biases":[36],"introduced":[37],"dataset":[39],"imbalances.":[40],"To":[41],"address":[42],"this":[43],"issue,":[44],"we":[45],"propose":[46],"a":[47,81],"novel":[48],"framework":[49,59],"that":[50,121],"incorporates":[51],"causal":[52],"intervention":[53],"to":[54,112],"mitigate":[55],"spurious":[56],"correlations.":[57],"Our":[58],"enables":[60],"automatic":[62],"deconfounded":[65,114],"features":[66],"large-scale":[68],"records.":[70],"Two":[71],"key":[72],"stages":[73],"included":[75],"in":[76],"proposed":[78,123],"approach.":[79],"First,":[80],"baseline":[82],"model":[83],"is":[84],"constructed,":[85],"leveraging":[86],"Bidirectional":[87],"Encoder":[88],"Representations":[89],"Transformers":[91],"Long-Short-Term":[93],"Memory":[94],"architectures":[95],"semantic":[97],"classification":[99],"extraction.":[101],"Second,":[102],"data":[103],"augmentation,":[104],"interaction,":[106],"knowledge-embedding":[108],"techniques":[109],"used":[111],"derive":[113],"textual":[115],"features.":[116],"The":[117],"experimental":[118],"results":[119],"demonstrate":[120],"our":[122],"approach":[124],"significantly":[125],"improves":[126],"diagnostic":[127],"accuracy":[128],"enhances":[130],"robustness":[132],"similar":[134],"identification.":[136]},"counts_by_year":[],"updated_date":"2026-01-30T23:21:52.101496","created_date":"2026-01-30T00:00:00"}
