{"id":"https://openalex.org/W4220813721","doi":"https://doi.org/10.1145/3494566","title":"Intelligent Data Analysis using Optimized Support Vector Machine Based Data Mining Approach for Tourism Industry","display_name":"Intelligent Data Analysis using Optimized Support Vector Machine Based Data Mining Approach for Tourism Industry","publication_year":2022,"publication_date":"2022-03-09","ids":{"openalex":"https://openalex.org/W4220813721","doi":"https://doi.org/10.1145/3494566"},"language":"en","primary_location":{"id":"doi:10.1145/3494566","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3494566","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","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/A5043148206","display_name":"Ms Promila Sharma","orcid":"https://orcid.org/0000-0001-9723-7511"},"institutions":[{"id":"https://openalex.org/I49702814","display_name":"Mewar University","ror":"https://ror.org/01qva9798","country_code":"IN","type":"education","lineage":["https://openalex.org/I49702814"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Ms Promila Sharma","raw_affiliation_strings":["Department of Computer Science, Mewar University, Rajasthan, India"],"raw_orcid":"https://orcid.org/0000-0001-9723-7511","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Mewar University, Rajasthan, India","institution_ids":["https://openalex.org/I49702814"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026022675","display_name":"Uma Meena","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Uma Meena","raw_affiliation_strings":["Department of Computer Science and Engineering, SRMIST, Ghaziabad, Modinagar, Uttar Pradesh"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, SRMIST, Ghaziabad, Modinagar, Uttar Pradesh","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067482734","display_name":"Girish Sharma","orcid":"https://orcid.org/0000-0003-4512-8932"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Girish Kumar Sharma","raw_affiliation_strings":["Department of Computer Applications, Bhai Parmanand Institute of Business Studies (Under DTTE) GNCT of Delhi, Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Applications, Bhai Parmanand Institute of Business Studies (Under DTTE) GNCT of Delhi, Delhi, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043148206"],"corresponding_institution_ids":["https://openalex.org/I49702814"],"apc_list":null,"apc_paid":null,"fwci":5.542,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.95474914,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"16","issue":"5","first_page":"1","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10609","display_name":"Digital Marketing and Social Media","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10609","display_name":"Digital Marketing and Social Media","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12651","display_name":"Halal products and consumer behavior","score":0.9865000247955322,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14064","display_name":"Organizational and Employee Performance","score":0.9648000001907349,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7517106533050537},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7420241236686707},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7286979556083679},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.5430026650428772},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49166327714920044},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4136753976345062},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4091438055038452},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3864651620388031},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2397943139076233}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7517106533050537},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7420241236686707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7286979556083679},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5430026650428772},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49166327714920044},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4136753976345062},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4091438055038452},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3864651620388031},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2397943139076233}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3494566","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3494566","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.550000011920929}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W2317515691","https://openalex.org/W2408246687","https://openalex.org/W2417999172","https://openalex.org/W2460286025","https://openalex.org/W2503126809","https://openalex.org/W2520828129","https://openalex.org/W2549726853","https://openalex.org/W2556247010","https://openalex.org/W2560070550","https://openalex.org/W2586068811","https://openalex.org/W2593914038","https://openalex.org/W2742162950","https://openalex.org/W2798990976","https://openalex.org/W2889095026","https://openalex.org/W2890992808","https://openalex.org/W2891382305","https://openalex.org/W2899465786","https://openalex.org/W2924217342","https://openalex.org/W2943402144","https://openalex.org/W2944152053","https://openalex.org/W2947468187","https://openalex.org/W2963825799","https://openalex.org/W2964069209","https://openalex.org/W2967475656","https://openalex.org/W2982453621","https://openalex.org/W2983870531","https://openalex.org/W2985878620","https://openalex.org/W2986188410","https://openalex.org/W2999582513","https://openalex.org/W3000646835","https://openalex.org/W3011016572","https://openalex.org/W3014870144","https://openalex.org/W3022935508","https://openalex.org/W3024839251","https://openalex.org/W3034844260","https://openalex.org/W3035614918","https://openalex.org/W3039503982","https://openalex.org/W3090369369","https://openalex.org/W3106140273","https://openalex.org/W3118913631","https://openalex.org/W3129020919"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W4378510483","https://openalex.org/W2989932438","https://openalex.org/W4387297750","https://openalex.org/W2186333919"],"abstract_inverted_index":{"Data":[0],"analysis":[1,40,43,206],"involves":[2],"the":[3,27,32,50,62,74,90,127,135,141,151,157,163,168,175,184,188,193,198,201,211,214,218,221,233,237,244,247],"deployment":[4],"of":[5,29,76,200,213,246],"sophisticated":[6],"approaches":[7],"from":[8,31,140,187],"data":[9,42,68,77,95,112,131,152,159],"mining":[10,69,96,113],"methods,":[11],"information":[12,58],"theory,":[13],"and":[14,23,34,55,64,137,229],"artificial":[15],"intelligence":[16],"in":[17,92,117,126,150,155,177],"various":[18],"fields":[19],"like":[20],"tourism,":[21,38],"hospitality,":[22],"so":[24],"on":[25],"for":[26,48,73,162,197,236,250],"extraction":[28],"knowledge":[30,60],"gathered":[33],"preprocessed":[35],"data.":[36,66,143,190],"In":[37],"pattern":[39,186,251],"or":[41,59,78],"using":[44],"classification":[45,75,97],"is":[46,115,124,148,174,180,192,207,242],"significant":[47,158],"finding":[49],"patterns":[51],"that":[52],"represent":[53],"new":[54],"potentially":[56],"useful":[57,185],"about":[61],"destination":[63],"other":[65],"Several":[67],"techniques":[70],"are":[71,89,160],"introduced":[72],"patterns.":[79],"However,":[80],"overfitting,":[81],"less":[82],"accuracy,":[83,226],"local":[84],"minima,":[85],"sensitive":[86],"to":[87,133,166,182,209],"noise":[88,136],"drawbacks":[91],"some":[93],"existing":[94,234],"methods.":[98],"To":[99],"overcome":[100],"these":[101],"challenges,":[102],"Support":[103],"vector":[104],"machine":[105],"with":[106],"Red":[107],"deer":[108],"optimization":[109],"(SVM-RDO)":[110],"based":[111],"strategy":[114],"proposed":[116,181,202,215,222,248],"this":[118],"article.":[119],"Extended":[120],"Kalman":[121],"filter":[122],"(EKF)":[123],"utilized":[125],"first":[128],"phase,":[129,154],"i.e.,":[130],"cleaning":[132],"remove":[134],"missing":[138],"values":[139],"input":[142],"Mantaray":[144],"foraging":[145],"algorithm":[146],"(MaFA)":[147],"used":[149,196],"selection":[153],"which":[156,178],"selected":[161,189],"further":[164],"process":[165],"reduce":[167],"computational":[169],"complexity.":[170],"The":[171,204],"final":[172],"phase":[173],"classification,":[176],"SVM-RDO":[179,223,249],"access":[183],"PYTHON":[191],"implementation":[194],"tool":[195],"experiment":[199],"model.":[203],"experimental":[205,219],"done":[208],"show":[210],"efficacy":[212],"work.":[216],"From":[217],"results,":[220],"achieved":[224],"better":[225],"precision,":[227],"recall,":[228],"F1":[230],"score":[231],"than":[232],"methods":[235],"tourism":[238],"dataset.":[239],"Thus,":[240],"it":[241],"showed":[243],"effectiveness":[245],"analysis.":[252]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
