{"id":"https://openalex.org/W4385198354","doi":"https://doi.org/10.3389/fdata.2023.1200840","title":"Ki-Cook: clustering multimodal cooking representations through knowledge-infused learning","display_name":"Ki-Cook: clustering multimodal cooking representations through knowledge-infused learning","publication_year":2023,"publication_date":"2023-07-24","ids":{"openalex":"https://openalex.org/W4385198354","doi":"https://doi.org/10.3389/fdata.2023.1200840","pmid":"https://pubmed.ncbi.nlm.nih.gov/37554262"},"language":"en","primary_location":{"id":"doi:10.3389/fdata.2023.1200840","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3389/fdata.2023.1200840","pdf_url":"https://www.frontiersin.org/articles/10.3389/fdata.2023.1200840/pdf","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/articles/10.3389/fdata.2023.1200840/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061795720","display_name":"Revathy Venkataramanan","orcid":"https://orcid.org/0000-0002-5642-3438"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Revathy Venkataramanan","raw_affiliation_strings":["Department of Computer Science, Artificial Intelligence Research Institute, University of South Carolina, Columbia, SC, United States"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Artificial Intelligence Research Institute, University of South Carolina, Columbia, SC, United States","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060884184","display_name":"Swati Padhee","orcid":"https://orcid.org/0000-0001-5461-601X"},"institutions":[{"id":"https://openalex.org/I19648265","display_name":"Wright State University","ror":"https://ror.org/04qk6pt94","country_code":"US","type":"education","lineage":["https://openalex.org/I19648265"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Swati Padhee","raw_affiliation_strings":["Department of Computer Science, Wright State University, Dayton, OH, United States"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Wright State University, Dayton, OH, United States","institution_ids":["https://openalex.org/I19648265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111013407","display_name":"Saini Rohan Rao","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Saini Rohan Rao","raw_affiliation_strings":["Department of Computational Science and Engineering, Technical University of Munich, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computational Science and Engineering, Technical University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010096373","display_name":"Ronak Kaoshik","orcid":null},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ronak Kaoshik","raw_affiliation_strings":["Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, United States"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, United States","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108302865","display_name":"Anirudh Sundara Rajan","orcid":null},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anirudh Sundara Rajan","raw_affiliation_strings":["Department of Computer Science, University of Wisconsin Madison, Madison, WI, United States"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Wisconsin Madison, Madison, WI, United States","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028772801","display_name":"Amit Sheth","orcid":null},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amit Sheth","raw_affiliation_strings":["Department of Computer Science, Artificial Intelligence Research Institute, University of South Carolina, Columbia, SC, United States"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Artificial Intelligence Research Institute, University of South Carolina, Columbia, SC, United States","institution_ids":["https://openalex.org/I155781252"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5061795720"],"corresponding_institution_ids":["https://openalex.org/I155781252"],"apc_list":{"value":1150,"currency":"USD","value_usd":1150},"apc_paid":{"value":1150,"currency":"USD","value_usd":1150},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09062236,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":null,"first_page":"1200840","last_page":"1200840"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11584","display_name":"Biochemical Analysis and Sensing Techniques","score":0.984499990940094,"subfield":{"id":"https://openalex.org/subfields/2916","display_name":"Nutrition and Dietetics"},"field":{"id":"https://openalex.org/fields/29","display_name":"Nursing"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11925","display_name":"Culinary Culture and Tourism","score":0.9769999980926514,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/recipe","display_name":"Recipe","score":0.9250411987304688},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6332498788833618},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5997539162635803},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5870930552482605},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5449421405792236},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4555680453777313},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.43876782059669495},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4065147340297699},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3930496275424957},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3282570242881775},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18417826294898987},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10345989465713501}],"concepts":[{"id":"https://openalex.org/C2778671685","wikidata":"https://www.wikidata.org/wiki/Q219239","display_name":"Recipe","level":2,"score":0.9250411987304688},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6332498788833618},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5997539162635803},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5870930552482605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5449421405792236},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4555680453777313},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.43876782059669495},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4065147340297699},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3930496275424957},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3282570242881775},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18417826294898987},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10345989465713501},{"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3389/fdata.2023.1200840","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3389/fdata.2023.1200840","pdf_url":"https://www.frontiersin.org/articles/10.3389/fdata.2023.1200840/pdf","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},{"id":"pmid:37554262","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37554262","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in big data","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10406211","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10406211","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10406211/pdf/fdata-06-1200840.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Front Big Data","raw_type":"Text"},{"id":"pmh:oai:scholarcommons.sc.edu:aii_fac_pub-1610","is_oa":true,"landing_page_url":"https://scholarcommons.sc.edu/aii_fac_pub/591","pdf_url":null,"source":{"id":"https://openalex.org/S4306401386","display_name":"Scholar Commons (University of South Carolina)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I155781252","host_organization_name":"University of South Carolina","host_organization_lineage":["https://openalex.org/I155781252"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Publications","raw_type":"text"},{"id":"pmh:oai:doaj.org/article:b977b7c43e874936899d752772c0e8d5","is_oa":true,"landing_page_url":"https://doaj.org/article/b977b7c43e874936899d752772c0e8d5","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Big Data, Vol 6 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/fdata.2023.1200840","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3389/fdata.2023.1200840","pdf_url":"https://www.frontiersin.org/articles/10.3389/fdata.2023.1200840/pdf","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4049666403","display_name":null,"funder_award_id":"EAGER","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6290369538","display_name":null,"funder_award_id":"2133842","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320310846","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385198354.pdf","grobid_xml":"https://content.openalex.org/works/W4385198354.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2019933371","https://openalex.org/W2108598243","https://openalex.org/W2321687257","https://openalex.org/W2526198870","https://openalex.org/W2901369207","https://openalex.org/W2972610293","https://openalex.org/W2977680040","https://openalex.org/W3003973800","https://openalex.org/W3006287130","https://openalex.org/W3033103428","https://openalex.org/W3080321944","https://openalex.org/W3084852986","https://openalex.org/W3105032386","https://openalex.org/W3112165001","https://openalex.org/W3116705075","https://openalex.org/W3120468617","https://openalex.org/W3121800880","https://openalex.org/W3163303044","https://openalex.org/W3164325351","https://openalex.org/W3206660842","https://openalex.org/W3217675893","https://openalex.org/W4200629808","https://openalex.org/W4205511145","https://openalex.org/W4234552385","https://openalex.org/W4286899990","https://openalex.org/W4394646531","https://openalex.org/W6600669433","https://openalex.org/W6631190155","https://openalex.org/W6737478050","https://openalex.org/W6741536201","https://openalex.org/W6750704779","https://openalex.org/W6758539934","https://openalex.org/W6762635042","https://openalex.org/W6763152908","https://openalex.org/W6765062968","https://openalex.org/W6768868228","https://openalex.org/W6769127844","https://openalex.org/W6771957062","https://openalex.org/W6775983405","https://openalex.org/W6780226713","https://openalex.org/W6781074949","https://openalex.org/W6782480777","https://openalex.org/W6788119346","https://openalex.org/W6791793481","https://openalex.org/W6803039540","https://openalex.org/W6809712910"],"related_works":["https://openalex.org/W258429745","https://openalex.org/W3161239248","https://openalex.org/W2561508161","https://openalex.org/W3195543079","https://openalex.org/W2098178683","https://openalex.org/W2740680361","https://openalex.org/W3207562294","https://openalex.org/W2604742737","https://openalex.org/W4386893202","https://openalex.org/W4388686419"],"abstract_inverted_index":{"Cross-modal":[0],"recipe":[1,24,43,62,78,111,161,169],"retrieval":[2,204],"has":[3],"gained":[4],"prominence":[5],"due":[6],"to":[7,10,31,54,74,113,157,164,178,191,211,233,253,258,277],"its":[8],"ability":[9],"retrieve":[11,32,192],"a":[12,61,64,91,129,159,265],"text":[13],"representation":[14,18,133],"given":[15],"an":[16,196,208,246,282],"image":[17],"and":[19,57,81,89,110,166,225],"vice":[20],"versa.":[21],"Clustering":[22],"these":[23],"representations":[25,44,240],"based":[26,49],"on":[27,50,120,138],"similarity":[28,56,162],"is":[29,153,190],"essential":[30],"relevant":[33,193],"information":[34,194],"about":[35,72,87],"unknown":[36,197],"food":[37,198],"images.":[38],"Existing":[39],"studies":[40],"cluster":[41,167],"similar":[42,95,115,168,188,270],"in":[45,268,272],"the":[46,139,143,147,154,184,202,218,226,234,239,254,273,278,286],"latent":[47,274],"space":[48,275],"class":[51,65],"names.":[52],"Due":[53],"inter-class":[55],"intraclass":[58],"variation,":[59],"associating":[60],"with":[63,281],"name":[66],"does":[67],"not":[68],"provide":[69,84],"sufficient":[70],"knowledge":[71,86,104],"recipes":[73,88,189,271],"determine":[75],"similarity.":[76],"However,":[77],"title,":[79,112],"ingredients,":[80],"cooking":[82,132,144,181],"actions":[83],"detailed":[85],"are":[90],"better":[92],"determinant":[93,163],"of":[94,105,142,149,220,249,285,290],"recipes.":[96],"In":[97],"this":[98,102,125,152,259],"study,":[99],"we":[100,127,200],"utilized":[101],"additional":[103,247],"recipes,":[106,116],"such":[107],"as":[108],"ingredients":[109,251],"identify":[114,165],"emphasizing":[117],"attention":[118],"especially":[119],"rare":[121,250],"ingredients.":[122],"To":[123,146],"incorporate":[124],"knowledge,":[126,151],"propose":[128],"knowledge-infused":[130],"multimodal":[131,180],"learning":[134],"network,":[135],"Ki-Cook,":[136],"built":[137],"procedural":[140],"attribute":[141],"process.":[145],"best":[148],"our":[150,214,243,261],"first":[155],"study":[156],"adopt":[158],"comprehensive":[160],"representations.":[170],"The":[171],"proposed":[172,215],"network":[173],"also":[174],"incorporates":[175],"ingredient":[176,203],"images":[177],"learn":[179],"representation.":[182],"Since":[183],"motivation":[185],"for":[186,195],"clustering":[187,269],"image,":[199],"evaluated":[201],"task.":[205],"We":[206],"performed":[207],"empirical":[209],"analysis":[210],"establish":[212],"that":[213],"model":[216,244],"improves":[217],"Coverage":[219],"Ground":[221],"Truth":[222],"by":[223,230,242],"12%":[224],"Intersection":[227],"Over":[228],"Union":[229],"10%":[231],"compared":[232,252,276],"baseline":[235,255,279],"models.":[236,256],"On":[237],"average,":[238],"learned":[241],"contain":[245],"15.33%":[248],"Owing":[257],"difference,":[260],"qualitative":[262],"evaluation":[263],"shows":[264],"39%":[266],"improvement":[267],"models,":[280],"inter-annotator":[283],"agreement":[284],"Fleiss":[287],"kappa":[288],"score":[289],"0.35.":[291]},"counts_by_year":[],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
