{"id":"https://openalex.org/W4292103394","doi":"https://doi.org/10.1145/3552484.3555747","title":"Simulating Personal Food Consumption Patterns using a Modified Markov Chain","display_name":"Simulating Personal Food Consumption Patterns using a Modified Markov Chain","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4292103394","doi":"https://doi.org/10.1145/3552484.3555747"},"language":"en","primary_location":{"id":"doi:10.1145/3552484.3555747","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3552484.3555747","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3552484.3555747","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Workshop on Multimedia Assisted Dietary Management on Multimedia Assisted Dietary Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3552484.3555747","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035990918","display_name":"Xinyue Pan","orcid":"https://orcid.org/0000-0002-3791-9315"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinyue Pan","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063620170","display_name":"Jiangpeng He","orcid":"https://orcid.org/0000-0002-8552-9880"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiangpeng He","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111369129","display_name":"Andrew C. Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Peng","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001380619","display_name":"Fengqing Zhu","orcid":"https://orcid.org/0000-0002-3863-3220"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fengqing Zhu","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":5.2759,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.95223421,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"61","last_page":"69"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10866","display_name":"Nutritional Studies and Diet","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10866","display_name":"Nutritional Studies and Diet","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11925","display_name":"Culinary Culture and Tourism","score":0.9625999927520752,"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"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9452000260353088,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7397618293762207},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"Dynamic time warping","score":0.6972144842147827},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6501363515853882},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.6415019631385803},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5525052547454834},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5072386264801025},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4524579644203186},{"id":"https://openalex.org/keywords/maximum-entropy-markov-model","display_name":"Maximum-entropy Markov model","score":0.435397207736969},{"id":"https://openalex.org/keywords/image-warping","display_name":"Image warping","score":0.4315565824508667},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3996409475803375},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.3682490587234497},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.2911292612552643}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7397618293762207},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.6972144842147827},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6501363515853882},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.6415019631385803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5525052547454834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5072386264801025},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4524579644203186},{"id":"https://openalex.org/C196956702","wikidata":"https://www.wikidata.org/wiki/Q6795829","display_name":"Maximum-entropy Markov model","level":5,"score":0.435397207736969},{"id":"https://openalex.org/C157202957","wikidata":"https://www.wikidata.org/wiki/Q1659609","display_name":"Image warping","level":2,"score":0.4315565824508667},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3996409475803375},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.3682490587234497},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.2911292612552643}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3552484.3555747","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3552484.3555747","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3552484.3555747","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Workshop on Multimedia Assisted Dietary Management on Multimedia Assisted Dietary Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2208.06709","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2208.06709","pdf_url":"https://arxiv.org/pdf/2208.06709","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3552484.3555747","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3552484.3555747","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3552484.3555747","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Workshop on Multimedia Assisted Dietary Management on Multimedia Assisted Dietary Management","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","score":0.6299999952316284,"display_name":"Zero hunger"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4292103394.pdf","grobid_xml":"https://content.openalex.org/works/W4292103394.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W12634471","https://openalex.org/W1551258398","https://openalex.org/W1853374870","https://openalex.org/W2097117768","https://openalex.org/W2097820631","https://openalex.org/W2128160875","https://openalex.org/W2247585390","https://openalex.org/W2401231614","https://openalex.org/W2526198870","https://openalex.org/W2544747291","https://openalex.org/W2560828904","https://openalex.org/W2794393374","https://openalex.org/W2892022580","https://openalex.org/W2949650786","https://openalex.org/W2962835968","https://openalex.org/W2962901913","https://openalex.org/W2964137095","https://openalex.org/W3021903196","https://openalex.org/W3034451759","https://openalex.org/W3080950656","https://openalex.org/W3146950576","https://openalex.org/W3171007011","https://openalex.org/W3182381947","https://openalex.org/W3197028871","https://openalex.org/W3198052526","https://openalex.org/W3205553363","https://openalex.org/W4226103503","https://openalex.org/W4236965008","https://openalex.org/W4283331389","https://openalex.org/W4287024948","https://openalex.org/W4287556768","https://openalex.org/W4297749829"],"related_works":["https://openalex.org/W2134386692","https://openalex.org/W2379938888","https://openalex.org/W1510894296","https://openalex.org/W2116722627","https://openalex.org/W1977445474","https://openalex.org/W4233405330","https://openalex.org/W2194396582","https://openalex.org/W2082284720","https://openalex.org/W2566202039","https://openalex.org/W2799426416"],"abstract_inverted_index":{"Food":[0],"image":[1,42],"classification":[2,43],"serves":[3],"as":[4,135],"the":[5,38,82,121,139,145,161],"foundation":[6],"of":[7,40,50,84,97,108,141],"image-based":[8],"dietary":[9],"assessment":[10],"to":[11,35,57,74,137],"predict":[12],"food":[13,20,41,53,77],"categories.":[14],"Since":[15],"there":[16],"are":[17],"many":[18],"different":[19],"classes":[21],"in":[22],"real":[23],"life,":[24],"conventional":[25],"models":[26],"cannot":[27],"achieve":[28],"sufficiently":[29],"high":[30],"accuracy.":[31],"Personalized":[32],"classifiers":[33],"aim":[34],"largely":[36],"improve":[37],"accuracy":[39],"for":[44,61],"each":[45],"individual.":[46],"However,":[47],"a":[48,59,71,85,105],"lack":[49],"public":[51,146],"personal":[52,76],"consumption":[54,78],"data":[55,79,102,114,123],"proves":[56],"be":[58,117],"challenge":[60],"training":[62],"such":[63],"models.":[64],"To":[65],"address":[66],"this":[67],"issue,":[68],"we":[69,126],"propose":[70],"novel":[72],"framework":[73],"simulate":[75],"patterns,":[80],"leveraging":[81],"use":[83,127],"modified":[86],"Markov":[87,163],"chain":[88,164],"model":[89],"and":[90,111,132,160],"self-supervised":[91],"learning.":[92],"Our":[93,149],"method":[94,143],"is":[95],"capable":[96],"creating":[98],"an":[99],"accurate":[100],"future":[101],"pattern":[103],"from":[104],"limited":[106],"amount":[107],"initial":[109,122],"data,":[110],"our":[112,142],"simulated":[113],"patterns":[115],"can":[116],"closely":[118],"correlated":[119],"with":[120,157],"pattern.":[124],"Furthermore,":[125],"Dynamic":[128],"Time":[129],"Warping":[130],"distance":[131],"Kullback-Leibler":[133],"divergence":[134],"metrics":[136],"evaluate":[138],"effectiveness":[140],"on":[144],"Food-101":[147],"dataset.":[148],"ex-":[150],"perimental":[151],"results":[152],"demonstrate":[153],"promising":[154],"performance":[155],"compared":[156],"random":[158],"simulation":[159],"original":[162],"method.":[165]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2022-08-17T00:00:00"}