{"id":"https://openalex.org/W6998434959","doi":null,"title":"AI in Automotive Repair:Building a Data Driven Chatbot for Enhanced Vehicle Diagnostics","display_name":"AI in Automotive Repair:Building a Data Driven Chatbot for Enhanced Vehicle Diagnostics","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W6998434959"},"language":"en","primary_location":{"id":"pmh:oai:DiVA.org:ltu-107620","doi":null,"is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-107620","pdf_url":"https://ltu.diva-portal.org/smash/get/diva2:1872964/FULLTEXT01","source":{"id":"https://openalex.org/S4306400653","display_name":"Diva portal (Dalarna University Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/bachelorThesis"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://ltu.diva-portal.org/smash/get/diva2:1872964/FULLTEXT01","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Dash, Dipanwita","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Dash, Dipanwita","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.7050999999046326,"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/T10028","display_name":"Topic Modeling","score":0.7050999999046326,"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/T13904","display_name":"Artificial Intelligence Applications","score":0.12150000035762787,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.03420000150799751,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/automotive-repair","display_name":"automotive repair","score":0.9490000009536743},{"id":"https://openalex.org/keywords/vehicle-diagnostics","display_name":"vehicle diagnostics","score":0.9290000200271606},{"id":"https://openalex.org/keywords/chatbots","display_name":"chatbots","score":0.9020000100135803},{"id":"https://openalex.org/keywords/retrieval-augmented-generation","display_name":"retrieval-augmented generation","score":0.9670000076293945},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.9940000176429749},{"id":"https://openalex.org/keywords/repair-records","display_name":"repair records","score":0.46700000762939453},{"id":"https://openalex.org/keywords/vector-databases","display_name":"vector databases","score":0.4830000102519989},{"id":"https://openalex.org/keywords/milvus","display_name":"Milvus","score":0.8270000219345093},{"id":"https://openalex.org/keywords/cost-effectiveness","display_name":"cost-effectiveness","score":0.8050000071525574},{"id":"https://openalex.org/keywords/scalability","display_name":"scalability","score":0.671999990940094},{"id":"https://openalex.org/keywords/data-privacy","display_name":"data privacy","score":0.7059999704360962},{"id":"https://openalex.org/keywords/hybrid-ai-architecture","display_name":"hybrid AI architecture","score":0.35600000619888306}],"concepts":[{"id":"https://openalex.org/C2779041454","wikidata":"https://www.wikidata.org/wiki/Q870780","display_name":"Chatbot","level":2,"score":0.8859999775886536},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6680999994277954},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.5692999958992004},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.5674999952316284},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.49149999022483826},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.4408000111579895},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4000000059604645},{"id":"https://openalex.org/C180591934","wikidata":"https://www.wikidata.org/wiki/Q1253369","display_name":"Downtime","level":2,"score":0.3968999981880188},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.3431999981403351},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3427000045776367},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.3418999910354614},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C145804949","wikidata":"https://www.wikidata.org/wiki/Q478123","display_name":"Situation awareness","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.3206999897956848},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2962999939918518},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2903999984264374},{"id":"https://openalex.org/C25810664","wikidata":"https://www.wikidata.org/wiki/Q44325","display_name":"Ontology","level":2,"score":0.2888000011444092},{"id":"https://openalex.org/C111065885","wikidata":"https://www.wikidata.org/wiki/Q1189053","display_name":"Fuzz testing","level":3,"score":0.288100004196167},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2815999984741211},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27559998631477356},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C116537","wikidata":"https://www.wikidata.org/wiki/Q2169973","display_name":"Service provider","level":3,"score":0.26899999380111694},{"id":"https://openalex.org/C21285288","wikidata":"https://www.wikidata.org/wiki/Q2117885","display_name":"Systems Modeling Language","level":4,"score":0.26759999990463257},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.26759999990463257},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26249998807907104},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C509989072","wikidata":"https://www.wikidata.org/wiki/Q15188241","display_name":"Model-driven architecture","level":4,"score":0.2533000111579895},{"id":"https://openalex.org/C2778485113","wikidata":"https://www.wikidata.org/wiki/Q193231","display_name":"Debugger","level":3,"score":0.2524999976158142},{"id":"https://openalex.org/C180198813","wikidata":"https://www.wikidata.org/wiki/Q121182","display_name":"Information system","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:DiVA.org:ltu-107620","doi":null,"is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-107620","pdf_url":"https://ltu.diva-portal.org/smash/get/diva2:1872964/FULLTEXT01","source":{"id":"https://openalex.org/S4306400653","display_name":"Diva portal (Dalarna University Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/bachelorThesis"}],"best_oa_location":{"id":"pmh:oai:DiVA.org:ltu-107620","doi":null,"is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-107620","pdf_url":"https://ltu.diva-portal.org/smash/get/diva2:1872964/FULLTEXT01","source":{"id":"https://openalex.org/S4306400653","display_name":"Diva portal (Dalarna University Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/bachelorThesis"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5378999710083008}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W6998434959.pdf","grobid_xml":"https://content.openalex.org/works/W6998434959.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W2787560479","https://openalex.org/W2896457183","https://openalex.org/W2969389652","https://openalex.org/W3001279689","https://openalex.org/W3020712669","https://openalex.org/W3027879771","https://openalex.org/W3039017601","https://openalex.org/W3174809957","https://openalex.org/W3214978544","https://openalex.org/W4283026156","https://openalex.org/W4312089343","https://openalex.org/W4320005767","https://openalex.org/W4322718191","https://openalex.org/W4362515116","https://openalex.org/W4387156782","https://openalex.org/W4387561528","https://openalex.org/W4390723197","https://openalex.org/W4391158659","https://openalex.org/W4404534210"],"related_works":["https://openalex.org/W7001353320","https://openalex.org/W4416415118","https://openalex.org/W7155259345","https://openalex.org/W4413289880","https://openalex.org/W4387673633","https://openalex.org/W7167509370","https://openalex.org/W4416263533","https://openalex.org/W4400645432","https://openalex.org/W4416094543","https://openalex.org/W4411271920"],"abstract_inverted_index":{"Generative":[0],"Artificial":[1],"Intelligence":[2],"(AI)":[3],"and":[4,17,46,68,76,97,121,133,137,143,150,168,204,229,244,253,265,304,344],"Large":[5,184],"Language":[6,185],"Models":[7],"(LLMs)":[8],"present":[9],"a":[10,105,115,176,353],"promising":[11],"avenue":[12],"to":[13,81,93,148,155,166,182,287,331],"augment":[14,183],"service":[15,120,144,355],"delivery":[16],"customer":[18],"satisfaction":[19],"in":[20,30,63,73,251,262,292,311],"many":[21],"sectors,":[22],"including":[23],"automotive":[24,100,293],"repair.":[25],"The":[26,86,124,189,208,246,269,276],"traditional":[27],"diagnostic":[28],"systems":[29,236,351],"this":[31,90,157,163,280],"sector,":[32],"supporting":[33],"the":[34,55,95,152,160,196,213,218,233,256,288,333],"\"Triple":[35],"C\"":[36],"Complaint,":[37],"Cause,":[38],"Correction":[39],"(CCC)":[40],"of":[41,57,89,99,118,279,290,307,327,335,342],"capturing":[42],"Complaints,":[43],"identifying":[44],"Causes":[45],"providing":[47],"Corrections,":[48],"often":[49],"suffer":[50],"from":[51,59,114,128,130],"inefficiencies,":[52],"such":[53,298],"as":[54,232,299,338,340],"under-utilization":[56],"insights":[58],"historic":[60],"cases,":[61],"stored":[62],"massive":[64],"databases":[65],"containing":[66],"structured":[67],"unstructured":[69],"data.":[70],"This":[71],"results":[72],"increased":[74],"costs":[75],"extended":[77,345],"vehicle":[78,142,349],"downtime":[79],"due":[80],"repetitive":[82],"or":[83],"misdiagnosed":[84],"issues.":[85],"primary":[87],"objective":[88],"research":[91,281,318],"is":[92,126,249,260,282],"enhance":[94],"efficiency":[96],"accuracy":[98],"repair":[101,122],"services":[102],"by":[103,274],"developing":[104],"chatbot":[106,172],"system":[107,158,191,210,248,259,302],"which":[108],"can":[109],"retrieve":[110],"relevant":[111],"CCC":[112],"information":[113],"dataset":[116,125],"consisting":[117],"technician":[119],"entries.":[123],"sourced":[127],"workshops":[129],"several":[131],"countries,":[132],"includes":[134],"technical":[135],"codes":[136],"free":[138],"form":[139],"text":[140],"with":[141,347],"descriptions.":[145],"In":[146],"order":[147],"explore":[149],"overcome":[151],"infrastructure":[153],"challenges":[154],"implement":[156],"within":[159,212],"organizational":[161],"setup,":[162],"thesis":[164],"aims":[165],"develop":[167],"analyze":[169],"two":[170],"different":[171],"systems,":[173],"both":[174,336],"featuring":[175],"Retrieval":[177],"Augmented":[178],"Generation":[179],"(RAG)":[180],"framework":[181],"Model":[186],"(LLM)":[187],"outputs.":[188],"first":[190],"being":[192],"implemented":[193,273],"on-premises,":[194],"integrates":[195],"Instructor":[197],"XL":[198],"embedding":[199],"model,":[200],"Milvus":[201],"vector":[202,227],"database,":[203],"Mixtral":[205],"8x7B":[206],"LLM.":[207,234],"second":[209],"operates":[211],"Azure":[214,223],"cloud":[215,257],"environment,":[216],"employing":[217],"text-embedding-ada-002":[219],"model":[220],"for":[221,226,316,352],"embedding,":[222],"AI":[224,291,309],"Search":[225],"retrieval":[228],"GPT-3.5":[230],"Turbo":[231],"Both":[235],"are":[237],"evaluated":[238],"based":[239,258],"on":[240],"performance,":[241],"accuracy,":[242],"scalability,":[243,263,303],"cost-effectiveness.":[245],"on-premises":[247],"better":[250,261],"performance":[252],"cost-effectiveness,":[254],"however,":[255],"availability":[264],"using":[266],"searchable":[267],"metadata.":[268],"latter":[270],"has":[271],"been":[272],"me.":[275],"main":[277],"impact":[278],"demonstrated":[283],"through":[284],"its":[285],"contribution":[286],"integration":[289,346],"services,":[294],"addressing":[295],"critical":[296],"aspects":[297],"data":[300,350],"privacy,":[301],"practical":[305],"implementation":[306],"state-of-the-art":[308],"technologies":[310],"an":[312],"industry-specific":[313],"context.":[314],"Recommendations":[315],"future":[317],"include":[319],"language":[320],"support,":[321],"enhanced":[322],"interactions,":[323],"improved":[324],"evaluation,":[325],"exploration":[326],"hybrid":[328],"architectural":[329],"frameworks":[330],"combine":[332],"strengths":[334],"RAG":[337],"well":[339],"fine-tuning":[341],"LLM,":[343],"real-time":[348],"comprehensive":[354],"experience.":[356]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-10-10T00:00:00"}
