{"id":"https://openalex.org/W3036160116","doi":"https://doi.org/10.1109/icccs49078.2020.9118467","title":"Feature Selection and Reduction Based on SMOTE and Information Gain for Sentiment Mining","display_name":"Feature Selection and Reduction Based on SMOTE and Information Gain for Sentiment Mining","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W3036160116","doi":"https://doi.org/10.1109/icccs49078.2020.9118467","mag":"3036160116"},"language":"en","primary_location":{"id":"doi:10.1109/icccs49078.2020.9118467","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccs49078.2020.9118467","pdf_url":null,"source":{"id":"https://openalex.org/S4306498617","display_name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","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/A5050094115","display_name":"Patcharanikarn Pongthanoo","orcid":null},"institutions":[{"id":"https://openalex.org/I179193067","display_name":"Khon Kaen University","ror":"https://ror.org/03cq4gr50","country_code":"TH","type":"education","lineage":["https://openalex.org/I179193067"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Patcharanikarn Pongthanoo","raw_affiliation_strings":["Department of Computer Science, Khon Kaen University, Khon Kaen, Thailand"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Khon Kaen University, Khon Kaen, Thailand","institution_ids":["https://openalex.org/I179193067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035043749","display_name":"Wararat Songpan","orcid":"https://orcid.org/0000-0002-3813-6910"},"institutions":[{"id":"https://openalex.org/I179193067","display_name":"Khon Kaen University","ror":"https://ror.org/03cq4gr50","country_code":"TH","type":"education","lineage":["https://openalex.org/I179193067"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Wararat Songpan","raw_affiliation_strings":["Department of Computer Science, Khon Kaen University, Khon Kaen, Thailand"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Khon Kaen University, Khon Kaen, Thailand","institution_ids":["https://openalex.org/I179193067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5050094115"],"corresponding_institution_ids":["https://openalex.org/I179193067"],"apc_list":null,"apc_paid":null,"fwci":0.2206,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.50709904,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"109","last_page":"114"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9934999942779541,"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"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9921000003814697,"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":0.7351203560829163},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6943128108978271},{"id":"https://openalex.org/keywords/c4.5-algorithm","display_name":"C4.5 algorithm","score":0.6908652782440186},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.6401726603507996},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6297953128814697},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6077127456665039},{"id":"https://openalex.org/keywords/information-gain-ratio","display_name":"Information gain ratio","score":0.5880576968193054},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5007801055908203},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48385417461395264},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46661654114723206},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46286022663116455},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.46175456047058105},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.45916610956192017},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.45708560943603516},{"id":"https://openalex.org/keywords/information-gain","display_name":"Information gain","score":0.45643532276153564},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.41933467984199524},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.41674935817718506},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18982553482055664},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0890316367149353}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7351203560829163},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6943128108978271},{"id":"https://openalex.org/C52003472","wikidata":"https://www.wikidata.org/wiki/Q1022655","display_name":"C4.5 algorithm","level":4,"score":0.6908652782440186},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6401726603507996},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6297953128814697},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6077127456665039},{"id":"https://openalex.org/C202185110","wikidata":"https://www.wikidata.org/wiki/Q6031086","display_name":"Information gain ratio","level":3,"score":0.5880576968193054},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5007801055908203},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48385417461395264},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46661654114723206},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46286022663116455},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.46175456047058105},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.45916610956192017},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.45708560943603516},{"id":"https://openalex.org/C2983203078","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Information gain","level":2,"score":0.45643532276153564},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.41933467984199524},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.41674935817718506},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18982553482055664},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0890316367149353},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccs49078.2020.9118467","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccs49078.2020.9118467","pdf_url":null,"source":{"id":"https://openalex.org/S4306498617","display_name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2027306352","https://openalex.org/W2056596884","https://openalex.org/W2119876468","https://openalex.org/W2148143831","https://openalex.org/W2516702142","https://openalex.org/W2522808030","https://openalex.org/W2728494775","https://openalex.org/W2783089512","https://openalex.org/W2798742061","https://openalex.org/W2810133888","https://openalex.org/W2890551119","https://openalex.org/W2911774765","https://openalex.org/W4323285610","https://openalex.org/W4323285617","https://openalex.org/W6678093348"],"related_works":["https://openalex.org/W2997511728","https://openalex.org/W4285406884","https://openalex.org/W3127626731","https://openalex.org/W3043530913","https://openalex.org/W3003720309","https://openalex.org/W2915012007","https://openalex.org/W3094470751","https://openalex.org/W2991884048","https://openalex.org/W4390843811","https://openalex.org/W2588019384"],"abstract_inverted_index":{"The":[0,34,125],"problem":[1],"of":[2,36,45,48,57,90,104,123,137,149,155,161,166,180,193,201,209,217],"classifying":[3,23],"the":[4,15,19,24,28,43,66,80,88,121,131,135,141,144,147,152,158,164,172,175,178,184,190,194,198,215],"sentiment":[5,185],"analysis":[6],"was":[7,39,98,128,151],"found":[8],"that":[9,17,171,196],"there":[10],"were":[11],"many":[12],"features":[13,47,182],"for":[14,26,31,51,134,183],"sentiments":[16],"caused":[18],"less":[20],"accuracy":[21,91,136,150],"in":[22,76,92],"sentiment,":[25],"example":[27],"negative":[29,145],"class":[30,50,139],"those":[32],"sentiments.":[33],"purpose":[35],"this":[37,84,167],"study":[38],"to":[40,64,70,78,119],"Figure":[41],"out":[42],"amount":[44],"suitable":[46,181,219],"each":[49,138],"learning":[52],"data":[53],"with":[54],"applied":[55],"integration":[56],"information":[58],"gain":[59],"(IG)":[60],"technique":[61,74],"which":[62],"used":[63],"reduce":[65],"factor":[67],"and":[68,95,114,143,157,174,206,214],"integrated":[69],"synthetic":[71],"minority":[72],"over-sampling":[73],"(SMOTE)":[75],"order":[77],"adjust":[79],"imbalanced":[81],"class.":[82],"In":[83],"study,":[85,168],"it":[86,97,169],"enhanced":[87],"efficiency":[89,122,148,192],"every":[93],"class,":[94],"then":[96],"evaluated":[99],"by":[100,220],"four":[101],"methods":[102],"consisting":[103],"J48,":[105],"Na\u00efve":[106],"Bayes,":[107],"k-Nearest":[108],"Neighbor":[109],"where":[110],"k=1,":[111],"2,":[112],"3,":[113],"Support":[115],"Vector":[116],"Machine":[117],"(SVM)":[118],"compare":[120],"accuracy.":[124],"TP":[126,153,159,199,207],"Rate":[127,154,160,200,208],"employed":[129],"as":[130,203,211],"evaluation":[132],"metric":[133],"including":[140],"positive":[142],"whereas":[146],"Positive":[156,202],"Negative.":[162],"As":[163],"results":[165],"revealed":[170],"IG":[173],"SMOTE":[176,218],"suggested":[177],"number":[179],"analysis.":[186],"SVM":[187],"method":[188],"given":[189],"higher":[191],"accuracy,":[195],"obtained":[197],"86.50":[204],"%":[205,213],"Negative":[210],"89.10":[212],"level":[216],"300":[221],"%.":[222]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}