{"id":"https://openalex.org/W4414123616","doi":"https://doi.org/10.1109/fuzz62266.2025.11152046","title":"Enriching Pre-Training Using Fuzzy Logic","display_name":"Enriching Pre-Training Using Fuzzy Logic","publication_year":2025,"publication_date":"2025-07-06","ids":{"openalex":"https://openalex.org/W4414123616","doi":"https://doi.org/10.1109/fuzz62266.2025.11152046"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz62266.2025.11152046","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz62266.2025.11152046","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Fuzzy Systems (FUZZ)","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/A5076826113","display_name":"Vivek Kumar Gupta","orcid":"https://orcid.org/0000-0003-4404-3187"},"institutions":[{"id":"https://openalex.org/I56404289","display_name":"Indian Institute of Technology BHU","ror":"https://ror.org/01kh5gc44","country_code":"IN","type":"education","lineage":["https://openalex.org/I56404289"]},{"id":"https://openalex.org/I91357014","display_name":"Banaras Hindu University","ror":"https://ror.org/04cdn2797","country_code":"IN","type":"education","lineage":["https://openalex.org/I91357014"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Vansh Gupta","raw_affiliation_strings":["Indian Institute of Technology BHU,Department of Physics,Varanasi,India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology BHU,Department of Physics,Varanasi,India","institution_ids":["https://openalex.org/I56404289","https://openalex.org/I91357014"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063452654","display_name":"Vandana Bharti","orcid":"https://orcid.org/0000-0001-8899-4908"},"institutions":[{"id":"https://openalex.org/I4210152718","display_name":"Indian Institute of Technology Dharwad","ror":"https://ror.org/0509djg30","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210152718"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vandana Bharti","raw_affiliation_strings":["Indian Institute of Technology,Department of Computer Science and Engineering,Dharwad,India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology,Department of Computer Science and Engineering,Dharwad,India","institution_ids":["https://openalex.org/I4210152718"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103879137","display_name":"Abhinav Kumar","orcid":null},"institutions":[{"id":"https://openalex.org/I119241673","display_name":"Indian Institute of Technology Ropar","ror":"https://ror.org/02qkhhn56","country_code":"IN","type":"education","lineage":["https://openalex.org/I119241673"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Abhinav Kumar","raw_affiliation_strings":["Indian Institute of Technology Ropar,School of Artificial Intelligence and Data Engineering,Rupnagar,India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Ropar,School of Artificial Intelligence and Data Engineering,Rupnagar,India","institution_ids":["https://openalex.org/I119241673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079960440","display_name":"Anshul Sharma","orcid":"https://orcid.org/0000-0001-9313-9850"},"institutions":[{"id":"https://openalex.org/I9747756","display_name":"Atal Bihari Vajpayee Indian Institute of Information Technology and Management","ror":"https://ror.org/008b3ap06","country_code":"IN","type":"education","lineage":["https://openalex.org/I9747756"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anshul Sharma","raw_affiliation_strings":["ABV-Indian Institute of Information Technology & Management,Department of Information Technology,Gwalior,India"],"affiliations":[{"raw_affiliation_string":"ABV-Indian Institute of Information Technology & Management,Department of Information Technology,Gwalior,India","institution_ids":["https://openalex.org/I9747756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085601592","display_name":"Sanjay Kumar Singh","orcid":"https://orcid.org/0000-0002-8070-7350"},"institutions":[{"id":"https://openalex.org/I91357014","display_name":"Banaras Hindu University","ror":"https://ror.org/04cdn2797","country_code":"IN","type":"education","lineage":["https://openalex.org/I91357014"]},{"id":"https://openalex.org/I56404289","display_name":"Indian Institute of Technology BHU","ror":"https://ror.org/01kh5gc44","country_code":"IN","type":"education","lineage":["https://openalex.org/I56404289"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sanjay Kumar Singh","raw_affiliation_strings":["Indian Institute of Technology BHU,Department of Computer Science and Engineering,Varanasi,India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology BHU,Department of Computer Science and Engineering,Varanasi,India","institution_ids":["https://openalex.org/I56404289","https://openalex.org/I91357014"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5076826113"],"corresponding_institution_ids":["https://openalex.org/I56404289","https://openalex.org/I91357014"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36892257,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14025","display_name":"Educational Technology and Assessment","score":0.9954000115394592,"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"}},"topics":[{"id":"https://openalex.org/T14025","display_name":"Educational Technology and Assessment","score":0.9954000115394592,"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"}},{"id":"https://openalex.org/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","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"}},{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9894000291824341,"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/robustness","display_name":"Robustness (evolution)","score":0.5271000266075134},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5249000191688538},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49889999628067017},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.4593000113964081},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4408999979496002},{"id":"https://openalex.org/keywords/statistical-relational-learning","display_name":"Statistical relational learning","score":0.4262000024318695},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.421999990940094},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3440999984741211},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3431999981403351}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6873999834060669},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5633999705314636},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5271000266075134},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5249000191688538},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49889999628067017},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.4593000113964081},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4408999979496002},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.426800012588501},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.4262000024318695},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.421999990940094},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3709999918937683},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3431999981403351},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.335999995470047},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.3292999863624573},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3269999921321869},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.31450000405311584},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C140146324","wikidata":"https://www.wikidata.org/wiki/Q1144319","display_name":"Predicate (mathematical logic)","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.27390000224113464},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2540999948978424},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz62266.2025.11152046","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz62266.2025.11152046","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Fuzzy Systems (FUZZ)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1995450389","https://openalex.org/W2012257195","https://openalex.org/W2046738003","https://openalex.org/W2079325629","https://openalex.org/W2108614537","https://openalex.org/W2130915832","https://openalex.org/W2154851992","https://openalex.org/W2294347342","https://openalex.org/W2299467264","https://openalex.org/W2607500032","https://openalex.org/W2903329593","https://openalex.org/W2962756421","https://openalex.org/W2964015378","https://openalex.org/W2999246302","https://openalex.org/W3104097132","https://openalex.org/W4293651439","https://openalex.org/W4297733535","https://openalex.org/W4307929521","https://openalex.org/W4323338660","https://openalex.org/W4387717717","https://openalex.org/W4391506277"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W230091440","https://openalex.org/W2390279801","https://openalex.org/W2233261550","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2810751659"],"abstract_inverted_index":{"Graph":[0],"representation":[1],"learning":[2,6],"advances":[3],"graph":[4,45],"machine":[5],"by":[7,28],"encoding":[8],"structural":[9,57],"and":[10,32,39,69,108,126,146],"relational":[11],"information":[12],"into":[13,91],"feature":[14,113],"vectors.":[15],"This":[16],"study":[17],"introduces":[18],"a":[19,72],"fuzzy":[20],"logic-based":[21],"pre-processing":[22],"layer":[23,36,63,102],"that":[24,53],"enhances":[25],"node":[26,112],"representations":[27,149],"adding":[29],"semantic":[30,42],"diversity":[31],"contextual":[33],"understanding.":[34],"The":[35,116],"models":[37],"uncertainty":[38],"captures":[40],"abstract":[41],"characteristics":[43],"in":[44,121],"data,":[46],"addressing":[47],"the":[48,62,92,100,135],"limitations":[49],"of":[50,75],"conventional":[51],"methods":[52],"depend":[54],"solely":[55],"on":[56,103],"attributes.":[58],"By":[59],"applying":[60],"defuzzification,":[61],"refines":[64],"embeddings,":[65],"improving":[66],"their":[67],"robustness":[68],"effectiveness":[70],"for":[71],"wide":[73],"range":[74],"downstream":[76],"tasks.":[77],"To":[78],"test":[79],"its":[80],"robustness,":[81],"we":[82],"introduce":[83],"Gaussian":[84],"noise":[85,130],"ranging":[86],"from":[87],"2%":[88],"to":[89,138],"10%":[90],"datasets,":[93],"simulating":[94],"real-world":[95],"data":[96],"imperfections.":[97],"We":[98],"evaluate":[99],"proposed":[101],"GraphMamba":[104],"architecture,":[105],"using":[106],"DeepWalk":[107],"Node2Vec":[109],"as":[110],"baseline":[111],"generation":[114],"algorithms.":[115],"results":[117],"show":[118],"consistent":[119],"improvements":[120],"accuracy,":[122],"F1":[123],"scores,":[124],"precision,":[125],"recall":[127],"across":[128],"different":[129],"levels.":[131],"Our":[132],"findings":[133],"demonstrate":[134],"layer\u2019s":[136],"ability":[137],"preserve":[139],"high":[140],"representational":[141],"quality,":[142],"speed":[143],"up":[144],"convergence,":[145],"handle":[147],"noisy":[148],"effectively.":[150]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}