{"id":"https://openalex.org/W2912318878","doi":"https://doi.org/10.1109/idap.2018.8620774","title":"Examining the Impact of Feature Selection on Classification of User Reviews in Web Pages","display_name":"Examining the Impact of Feature Selection on Classification of User Reviews in Web Pages","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2912318878","doi":"https://doi.org/10.1109/idap.2018.8620774","mag":"2912318878"},"language":"en","primary_location":{"id":"doi:10.1109/idap.2018.8620774","doi":"https://doi.org/10.1109/idap.2018.8620774","is_oa":false,"landing_page_url":"https://doi.org/10.1109/idap.2018.8620774","pdf_url":null,"source":{"id":"https://openalex.org/S4306498172","display_name":"International Artificial Intelligence and Data Processing Symposium (IDAP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"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":"2018 International Conference on Artificial Intelligence and Data Processing (IDAP)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5078816512","display_name":"Erdin\u00e7 Uzun","orcid":"https://orcid.org/0000-0003-4351-2244","observed_orcids":["https://orcid.org/0000-0003-4351-2244"]},"institutions":[{"id":"https://openalex.org/I125454184","display_name":"Tekirda\u011f Nam\u0131k Kemal University","ror":"https://ror.org/01a0mk874","country_code":"TR","type":"education","lineage":["https://openalex.org/I125454184"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Erdinc Uzun","raw_affiliation_strings":["Computer Engineering Faculty, Nam\u0131k Kemal University, Tekirda\u011f, \u00c7orlu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Engineering Faculty, Nam\u0131k Kemal University, Tekirda\u011f, \u00c7orlu","institution_ids":["https://openalex.org/I125454184"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061813863","display_name":"Erkan \u00d6zhan","orcid":"https://orcid.org/0000-0002-3971-2676","observed_orcids":["https://orcid.org/0000-0002-3971-2676"]},"institutions":[{"id":"https://openalex.org/I125454184","display_name":"Tekirda\u011f Nam\u0131k Kemal University","ror":"https://ror.org/01a0mk874","country_code":"TR","type":"education","lineage":["https://openalex.org/I125454184"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Erkan Ozhan","raw_affiliation_strings":["Computer Engineering Faculty, Nam\u0131k Kemal University, Tekirda\u011f, \u00c7orlu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Engineering Faculty, Nam\u0131k Kemal University, Tekirda\u011f, \u00c7orlu","institution_ids":["https://openalex.org/I125454184"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125454184"],"apc_list":null,"apc_paid":null,"fwci":0.3924,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63499582,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":"43","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.7202000021934509,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12016","display_name":"Web Data Mining and Analysis","score":0.7202000021934509,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.2612000107765198,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.0038999998942017555,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/online-reviews","display_name":"online reviews","score":0.7940000295639038},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.7609999775886536},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.7689999938011169},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.8019999861717224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8327112197875977},{"id":"https://openalex.org/C21959979","wikidata":"https://www.wikidata.org/wiki/Q36774","display_name":"Web page","level":2,"score":0.6473304629325867},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6451054811477661},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5738029479980469},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5388727784156799},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46947798132896423},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4592018723487854},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4301445484161377},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4268453121185303},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4185374677181244},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.4174210727214813},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.22682812809944153}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/idap.2018.8620774","doi":"https://doi.org/10.1109/idap.2018.8620774","is_oa":false,"landing_page_url":"https://doi.org/10.1109/idap.2018.8620774","pdf_url":null,"source":{"id":"https://openalex.org/S4306498172","display_name":"International Artificial Intelligence and Data Processing Symposium (IDAP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"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":"2018 International Conference on Artificial Intelligence and Data Processing (IDAP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W582829353","https://openalex.org/W1559557735","https://openalex.org/W1912982817","https://openalex.org/W1973930027","https://openalex.org/W1978381081","https://openalex.org/W1979350297","https://openalex.org/W1985258161","https://openalex.org/W1988790447","https://openalex.org/W2003477935","https://openalex.org/W2019441211","https://openalex.org/W2019577381","https://openalex.org/W2030968134","https://openalex.org/W2049488566","https://openalex.org/W2063147917","https://openalex.org/W2076910790","https://openalex.org/W2111574971","https://openalex.org/W2113242816","https://openalex.org/W2117694587","https://openalex.org/W2120101509","https://openalex.org/W2126372189","https://openalex.org/W2160222246","https://openalex.org/W2514393974","https://openalex.org/W2519011775","https://openalex.org/W2741613270"],"related_works":["https://openalex.org/W2401153089","https://openalex.org/W7019166415","https://openalex.org/W2041459465","https://openalex.org/W2362897144","https://openalex.org/W1426271590","https://openalex.org/W4231009905","https://openalex.org/W1975010334","https://openalex.org/W7097861779","https://openalex.org/W2267350511","https://openalex.org/W1436652029"],"abstract_inverted_index":{"The":[0,111,123],"user":[1,94],"reviews":[2],"in":[3,40],"web":[4,15,26,86],"pages":[5,87],"can":[6,64],"provide":[7],"useful":[8],"information":[9],"about":[10,150],"the":[11,14,37,93,106,117,131,136,140,144,153],"content":[12],"of":[13,36,92,108,113,130,149],"page":[16,27],"for":[17,32,70,90,135,152],"text":[18,82],"processing":[19],"applications.":[20,34],"Automatically":[21],"extracting":[22,91],"data":[23],"from":[24,59,85],"a":[25,29,46],"is":[28,43,88],"crucial":[30],"process":[31,42],"these":[33,109],"One":[35],"used":[38],"methods":[39,119],"this":[41,71,74,114],"to":[44,104],"construct":[45],"learning":[47],"model":[48],"with":[49],"an":[50,76],"appropriate":[51],"classification":[52,118,137],"method":[53],"using":[54],"features":[55,63,83,132],"that":[56,127],"are":[57,102,120,133],"derived":[58],"data.":[60],"However,":[61],"some":[62],"be":[65],"either":[66],"redundant":[67],"or":[68],"irrelevant":[69],"model.":[72],"In":[73],"study,":[75],"imbalanced":[77],"dataset":[78],"including":[79],"47":[80],"shallow":[81],"obtained":[84],"utilized":[89],"reviews.":[95],"Then,":[96],"various":[97],"well-known":[98],"feature":[99],"selection":[100],"techniques":[101],"applied":[103],"reduce":[105],"number":[107],"features.":[110],"effects":[112],"reduction":[115],"on":[116],"also":[121],"examined.":[122],"experimental":[124],"results":[125,146],"indicate":[126],"approximately":[128],"half":[129],"sufficient":[134],"task.":[138],"Additionally,":[139],"AdaBoost":[141],"classifier":[142],"gives":[143],"best":[145],"concerning":[147],"precision":[148],"0.930":[151],"review":[154],"layout":[155],"prediction.":[156]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-10-26T11:51:55.731654","created_date":"2019-02-21T00:00:00"}