{"id":"https://openalex.org/W2979806124","doi":"https://doi.org/10.1108/el-12-2018-0241","title":"Identification of critical factors for assessing the quality of restaurants using data mining approaches","display_name":"Identification of critical factors for assessing the quality of restaurants using data mining approaches","publication_year":2019,"publication_date":"2019-10-11","ids":{"openalex":"https://openalex.org/W2979806124","doi":"https://doi.org/10.1108/el-12-2018-0241","mag":"2979806124"},"language":"en","primary_location":{"id":"doi:10.1108/el-12-2018-0241","is_oa":false,"landing_page_url":"https://doi.org/10.1108/el-12-2018-0241","pdf_url":null,"source":{"id":"https://openalex.org/S902750600","display_name":"The Electronic Library","issn_l":"0264-0473","issn":["0264-0473","1758-616X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Electronic Library","raw_type":"journal-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/A5081073247","display_name":"Ahsan Mahmood","orcid":"https://orcid.org/0000-0002-1229-7484"},"institutions":[{"id":"https://openalex.org/I16076960","display_name":"COMSATS University Islamabad","ror":"https://ror.org/00nqqvk19","country_code":"PK","type":"education","lineage":["https://openalex.org/I16076960"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Ahsan Mahmood","raw_affiliation_strings":["Department of Computer Science, COMSATS Institute of Information Technology, Attock, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, COMSATS Institute of Information Technology, Attock, Pakistan","institution_ids":["https://openalex.org/I16076960"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073826651","display_name":"Hikmat Ullah Khan","orcid":"https://orcid.org/0000-0002-8178-6652"},"institutions":[{"id":"https://openalex.org/I16076960","display_name":"COMSATS University Islamabad","ror":"https://ror.org/00nqqvk19","country_code":"PK","type":"education","lineage":["https://openalex.org/I16076960"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Hikmat Ullah Khan","raw_affiliation_strings":["Department of Computer Science, COMSATS University Islamabad \u2013 Wah Campus, Wah Cantt, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, COMSATS University Islamabad \u2013 Wah Campus, Wah Cantt, Pakistan","institution_ids":["https://openalex.org/I16076960"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I16076960"],"apc_list":null,"apc_paid":null,"fwci":1.2679,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.81525831,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"37","issue":"6","first_page":"952","last_page":"969"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11957","display_name":"Food Safety and Hygiene","score":0.9629999995231628,"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"}},"topics":[{"id":"https://openalex.org/T11957","display_name":"Food Safety and Hygiene","score":0.9629999995231628,"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/T12486","display_name":"Food Supply Chain Traceability","score":0.9226999878883362,"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/support-vector-machine","display_name":"Support vector machine","score":0.6725967526435852},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6610018014907837},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5896835923194885},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5630776882171631},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5488336086273193},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5255666971206665},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4959426820278168},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4613194167613983},{"id":"https://openalex.org/keywords/originality","display_name":"Originality","score":0.45775163173675537},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.4526039659976959},{"id":"https://openalex.org/keywords/learning-vector-quantization","display_name":"Learning vector quantization","score":0.44757112860679626},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4444288909435272},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.4136108458042145},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.2658659517765045}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6725967526435852},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6610018014907837},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5896835923194885},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5630776882171631},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5488336086273193},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5255666971206665},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4959426820278168},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4613194167613983},{"id":"https://openalex.org/C2776950860","wikidata":"https://www.wikidata.org/wiki/Q2914681","display_name":"Originality","level":3,"score":0.45775163173675537},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.4526039659976959},{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.44757112860679626},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4444288909435272},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4136108458042145},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.2658659517765045},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C11012388","wikidata":"https://www.wikidata.org/wiki/Q170658","display_name":"Creativity","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/el-12-2018-0241","is_oa":false,"landing_page_url":"https://doi.org/10.1108/el-12-2018-0241","pdf_url":null,"source":{"id":"https://openalex.org/S902750600","display_name":"The Electronic Library","issn_l":"0264-0473","issn":["0264-0473","1758-616X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Electronic Library","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1968799619","https://openalex.org/W1976511850","https://openalex.org/W1979262687","https://openalex.org/W1983134975","https://openalex.org/W1992777957","https://openalex.org/W2001070223","https://openalex.org/W2001569578","https://openalex.org/W2009385507","https://openalex.org/W2036256527","https://openalex.org/W2046858834","https://openalex.org/W2070609991","https://openalex.org/W2100631457","https://openalex.org/W2137959503","https://openalex.org/W2138854216","https://openalex.org/W2330491661","https://openalex.org/W2561360825","https://openalex.org/W2562231314","https://openalex.org/W2562498401","https://openalex.org/W2566313994","https://openalex.org/W2580219088","https://openalex.org/W2584960492","https://openalex.org/W2612220790","https://openalex.org/W2739967997","https://openalex.org/W2782536238","https://openalex.org/W2787956672"],"related_works":["https://openalex.org/W4367336074","https://openalex.org/W4379620016","https://openalex.org/W3154045278","https://openalex.org/W3210764983","https://openalex.org/W4367335949","https://openalex.org/W4285162676","https://openalex.org/W2970562883","https://openalex.org/W4382052559","https://openalex.org/W3036529732","https://openalex.org/W2780266336"],"abstract_inverted_index":{"Purpose":[0],"The":[1,24,123,150,169,207,252,273],"purpose":[2],"of":[3,17,38,55,61,73,111,117,125,128,139,191,194,209,221,234,242],"this":[4,89,185],"paper":[5],"is":[6,130,212],"to":[7,30,47,83,106,239],"apply":[8],"state-of-the-art":[9],"machine":[10,25,92,177],"learning":[11,26,93],"techniques":[12,27],"for":[13,49,80],"assessing":[14],"the":[15,18,32,53,56,59,62,71,74,81,85,108,112,115,121,137,140,155,173,189,210,216,240,243,258,264,286],"quality":[16],"restaurants":[19,48,75,113,260],"using":[20,133,215],"restaurant":[21,57,160,195,235,271,283],"inspection":[22,50,129,161,167,196,200,236],"data.":[23],"are":[28,104,152,204,254,267,275],"applied":[29,105],"solve":[31],"real-world":[33,156,231],"problems":[34],"in":[35,256,270,278,282],"all":[36],"sphere":[37],"life.":[39],"Health":[40],"and":[41,51,76,100,142,197,202,224,261],"food":[42],"departments":[43],"pay":[44],"regular":[45],"visits":[46],"mark":[52],"condition":[54,72],"on":[58,114,154],"basis":[60,116],"inspection.":[63,122,272],"These":[64],"inspections":[65,284],"consider":[66],"many":[67],"factors":[68,127,193,265],"that":[69,164,172,199,237,266],"determine":[70],"make":[77],"it":[78],"possible":[79,280],"authorities":[82],"classify":[84,107],"restaurants.":[86],"Design/methodology/approach":[87],"In":[88],"paper,":[90],"standard":[91,217],"techniques,":[94],"support":[95,175],"vector":[96,144,176],"machines,":[97],"na\u00efve":[98],"Bayes":[99],"random":[101],"forest":[102],"classifiers":[103,211],"critical":[109],"level":[110],"features":[118],"identified":[119],"during":[120],"importance":[124,147,190],"different":[126,192],"determined":[131],"by":[132,214,250,285],"feature":[134,146],"selection":[135],"through":[136],"help":[138,262],"minimum-redundancy-maximum-relevance":[141],"linear":[143],"quantization":[145],"methods.":[148],"Findings":[149],"experiments":[151],"accomplished":[153],"New":[157],"York":[158],"City":[159],"data":[162,232],"set":[163,233],"contains":[165],"diverse":[166],"features.":[168,206],"results":[170,274],"show":[171],"nonlinear":[174],"achieves":[178],"better":[179],"accuracy":[180],"than":[181],"other":[182],"techniques.":[183],"Moreover,":[184],"research":[186,228],"study":[187],"investigates":[188],"finds":[198],"score":[201],"grade":[203],"significant":[205],"performance":[208,218],"measured":[213],"evaluation":[219],"measures":[220],"accuracy,":[222],"sensitivity":[223],"specificity.":[225],"Originality/value":[226],"This":[227],"uses":[229],"a":[230],"has,":[238],"best":[241,259],"authors\u2019":[244],"knowledge,":[245],"never":[246],"been":[247],"used":[248],"previously":[249],"researchers.":[251],"findings":[253],"helpful":[255],"identifying":[257,279],"finding":[263],"considered":[268],"important":[269,277],"also":[276],"biases":[281],"authorities.":[287]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
