{"id":"https://openalex.org/W4403865021","doi":"https://doi.org/10.1109/bigdataservice62917.2024.00025","title":"Enhancing Supply Chain Efficiency Through Retrieve-Augmented Generation Approach in Large Language Models","display_name":"Enhancing Supply Chain Efficiency Through Retrieve-Augmented Generation Approach in Large Language Models","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4403865021","doi":"https://doi.org/10.1109/bigdataservice62917.2024.00025"},"language":"en","primary_location":{"id":"doi:10.1109/bigdataservice62917.2024.00025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdataservice62917.2024.00025","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 10th International Conference on Big Data Computing Service and Machine Learning Applications (BigDataService)","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/A5101161301","display_name":"Beilei Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I1343180700","display_name":"Intel (United States)","ror":"https://ror.org/01ek73717","country_code":"US","type":"company","lineage":["https://openalex.org/I1343180700"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Beilei Zhu","raw_affiliation_strings":["Intel Corp.,Global Supply Chain,Hillsboro,Oregon,USA"],"affiliations":[{"raw_affiliation_string":"Intel Corp.,Global Supply Chain,Hillsboro,Oregon,USA","institution_ids":["https://openalex.org/I1343180700"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053228252","display_name":"Chandrasekar Vuppalapati","orcid":"https://orcid.org/0000-0003-2261-759X"},"institutions":[{"id":"https://openalex.org/I51504820","display_name":"San Jose State University","ror":"https://ror.org/04qyvz380","country_code":"US","type":"education","lineage":["https://openalex.org/I51504820"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chandrasekar Vuppalapati","raw_affiliation_strings":["Computer Engineering, San Jose State University,San Jose,USA"],"affiliations":[{"raw_affiliation_string":"Computer Engineering, San Jose State University,San Jose,USA","institution_ids":["https://openalex.org/I51504820"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101161301"],"corresponding_institution_ids":["https://openalex.org/I1343180700"],"apc_list":null,"apc_paid":null,"fwci":3.4842,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.92936884,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"117","last_page":"121"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9354000091552734,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9354000091552734,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7534257173538208},{"id":"https://openalex.org/keywords/supply-chain","display_name":"Supply chain","score":0.648841917514801},{"id":"https://openalex.org/keywords/chain","display_name":"Chain (unit)","score":0.42369064688682556},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40511706471443176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32916173338890076}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7534257173538208},{"id":"https://openalex.org/C108713360","wikidata":"https://www.wikidata.org/wiki/Q1824206","display_name":"Supply chain","level":2,"score":0.648841917514801},{"id":"https://openalex.org/C199185054","wikidata":"https://www.wikidata.org/wiki/Q552299","display_name":"Chain (unit)","level":2,"score":0.42369064688682556},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40511706471443176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32916173338890076},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdataservice62917.2024.00025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdataservice62917.2024.00025","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 10th International Conference on Big Data Computing Service and Machine Learning Applications (BigDataService)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W6777615688","https://openalex.org/W6779857854","https://openalex.org/W6782879696","https://openalex.org/W6784180246"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3204019825"],"abstract_inverted_index":{"This":[0,59],"paper":[1,209],"delves":[2],"into":[3],"the":[4,24,33,51,224],"fascinating":[5],"integration":[6,134],"of":[7,28,36,135],"Retrieval-Augmented":[8],"Generation":[9],"(RAG)":[10],"with":[11,32],"Large":[12],"Language":[13],"Models":[14],"(LLMs)":[15],"for":[16],"optimizing":[17,215],"supply":[18,56,146,172,204,216],"chain":[19,57,147,173,205,217],"management":[20,218],"operations.":[21],"RAG":[22,100,176],"combines":[23],"robust":[25,182],"retrieval":[26,30,70,93,138,201],"capabilities":[27],"information":[29,75],"systems":[31],"generative":[34,136],"prowess":[35],"neural":[37],"language":[38,89],"models":[39],"to":[40,54,72,115,144,214],"create":[41],"a":[42,64,69,77,81,211],"powerful":[43],"tool":[44],"that":[45,67,109,220],"bolsters":[46],"data":[47,123,156],"protection":[48],"while":[49,80],"expanding":[50],"knowledge":[52,78],"base":[53],"capture":[55],"intricacies.":[58],"innovative":[60],"methodology":[61],"revolves":[62],"around":[63],"dual-component":[65],"system":[66,190],"employs":[68],"module":[71,83],"pinpoint":[73],"relevant":[74],"from":[76,112],"base,":[79],"generation":[82],"crafts":[84],"contextualized":[85,102],"responses":[86],"using":[87],"large":[88],"models.":[90],"Through":[91],"iterative":[92],"strategies":[94],"and":[95,106,133,137,154,170,181,195,203],"tailored":[96],"chunk":[97],"optimization":[98],"techniques,":[99],"enables":[101],"analysis,":[103],"predictive":[104],"insights,":[105],"data-driven":[107],"decision-making":[108],"streamlines":[110],"processes":[111],"demand":[113],"forecasting":[114,162],"inventory":[116,164],"optimization.":[117],"An":[118],"experimental":[119],"setup":[120],"mimicking":[121],"enterprise":[122],"classification":[124],"assesses":[125],"RAG's":[126,142],"efficacy,":[127],"employing":[128],"recursive":[129],"retrieval,":[130],"multi-hop":[131],"querying,":[132],"processes.":[139],"Results":[140],"showcase":[141],"potential":[143],"revolutionize":[145],"logistics,":[148],"enhancing":[149],"operational":[150],"agility,":[151],"minimizing":[152],"disruptions,":[153],"fortifying":[155],"security.":[157],"The":[158],"impacts":[159],"span":[160],"improved":[161],"accuracy,":[163],"level":[165],"optimization,":[166],"supplier":[167],"risk":[168],"assessment,":[169],"comprehensive":[171],"reporting.":[174],"However,":[175],"necessitates":[177],"stringent":[178],"ethical":[179],"considerations":[180],"countermeasures":[183],"against":[184],"exploitation.":[185],"Future":[186],"work":[187],"centers":[188],"on":[189],"scalability,":[191],"advanced":[192],"evaluation":[193],"metrics,":[194],"interdisciplinary":[196],"collaboration":[197],"between":[198],"machine":[199],"learning,":[200],"systems,":[202],"domains.":[206],"Overall,":[207],"this":[208],"presents":[210],"groundbreaking":[212],"approach":[213],"operations":[219],"could":[221],"significantly":[222],"impact":[223],"industry's":[225],"future.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6}],"updated_date":"2026-03-24T08:02:53.985720","created_date":"2025-10-10T00:00:00"}