{"id":"https://openalex.org/W2824756605","doi":"https://doi.org/10.1504/ijnvo.2018.10014686","title":"Optimal neural network to enhance classification accuracy for mining online reviews and opinions using improved PSO","display_name":"Optimal neural network to enhance classification accuracy for mining online reviews and opinions using improved PSO","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2824756605","doi":"https://doi.org/10.1504/ijnvo.2018.10014686","mag":"2824756605"},"language":"en","primary_location":{"id":"doi:10.1504/ijnvo.2018.10014686","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijnvo.2018.10014686","pdf_url":null,"source":{"id":"https://openalex.org/S176261709","display_name":"International Journal of Networking and Virtual Organisations","issn_l":"1470-9503","issn":["1470-9503","1741-5225"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Networking and Virtual Organisations","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/A5103122624","display_name":"B. Dhanalakshmi","orcid":null},"institutions":[{"id":"https://openalex.org/I43814544","display_name":"Sathyabama Institute of Science and Technology","ror":"https://ror.org/01defpn95","country_code":"IN","type":"education","lineage":["https://openalex.org/I43814544"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"B. Dhanalakshmi","raw_affiliation_strings":["Department of Computer Science and Engineering, Sathyabama University, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Sathyabama University, Chennai, India","institution_ids":["https://openalex.org/I43814544"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033911878","display_name":"A. Chandrasekar","orcid":"https://orcid.org/0000-0002-3649-0959"},"institutions":[{"id":"https://openalex.org/I4210101093","display_name":"St. Joseph's Institute of Technology","ror":"https://ror.org/012npkr10","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210101093"]},{"id":"https://openalex.org/I4387154592","display_name":"St. Joseph\u2019s College of Engineering","ror":"https://ror.org/01g3pby21","country_code":null,"type":"education","lineage":["https://openalex.org/I4387154592"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arumugam Chandra Sekar","raw_affiliation_strings":["Department of Computer Science and Engineering, St. Joseph's College of Engineering, Old Mamallapuram Road, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, St. Joseph's College of Engineering, Old Mamallapuram Road, Chennai, India","institution_ids":["https://openalex.org/I4210101093","https://openalex.org/I4387154592"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103122624"],"corresponding_institution_ids":["https://openalex.org/I43814544"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07019542,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"4","first_page":"338","last_page":"338"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9320999979972839,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9320999979972839,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.92330002784729,"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":0.9082000255584717,"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/computer-science","display_name":"Computer science","score":0.783247709274292},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.769232988357544},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5335469841957092},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5208328366279602},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4669457674026489},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4653412103652954},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.4463563561439514},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.44492462277412415},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4314005374908447},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4106833338737488},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37683430314064026}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.783247709274292},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.769232988357544},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5335469841957092},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5208328366279602},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4669457674026489},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4653412103652954},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4463563561439514},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.44492462277412415},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4314005374908447},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4106833338737488},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37683430314064026},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1504/ijnvo.2018.10014686","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijnvo.2018.10014686","pdf_url":null,"source":{"id":"https://openalex.org/S176261709","display_name":"International Journal of Networking and Virtual Organisations","issn_l":"1470-9503","issn":["1470-9503","1741-5225"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Networking and Virtual Organisations","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2548633793","https://openalex.org/W3089396779","https://openalex.org/W3132372214","https://openalex.org/W2596247554","https://openalex.org/W4301373556","https://openalex.org/W2941935829","https://openalex.org/W2438765327","https://openalex.org/W3013279174","https://openalex.org/W4317653575","https://openalex.org/W4224284088"],"abstract_inverted_index":{"While":[0],"using":[1,38],"rapid":[2],"growth":[3],"from":[4,74],"World":[5],"Wide":[6],"Web,":[7],"there":[8],"is":[9],"volatile":[10],"improve":[11],"in":[12,77,106],"the":[13,75,80,89,95,109],"user-produced":[14],"subject":[15],"matter":[16],"such":[17,56,112],"as":[18,57,99,153],"purchaser":[19],"evaluations,":[20],"websites,":[21],"discussion":[22],"community":[23],"forums,":[24],"social":[25],"networks":[26],"and":[27,66,84,134,148],"so":[28],"forth":[29],"In":[30,52,79,88],"previous":[31,100],"work,":[32,91],"we":[33,92,140],"have":[34],"implemented":[35],"opinion":[36,47,50,118,121,135],"mining":[37],"three":[39,97],"phase.":[40],"They":[41],"are:":[42],"1)":[43,114],"data":[44,115],"pre-processing;":[45],"2)":[46,117],"extraction;":[48,119],"3)":[49,120],"mining.":[51,122],"feature":[53,132,138],"extraction,":[54,139],"features,":[55],"term":[58,70],"frequency,":[59],"part":[60],"of":[61,108],"speech":[62],"(POS),":[63],"syntax,":[64],"negation":[65],"term-based":[67],"features":[68,147],"beyond":[69],"unigrams":[71],"were":[72],"extracted":[73],"words":[76],"documents.":[78],"final":[81],"step,":[82],"ranking":[83],"classification":[85],"was":[86],"done.":[87],"present":[90],"will":[93,126],"implement":[94],"same":[96],"phases":[98],"work":[101],"but":[102],"with":[103],"different":[104],"process":[105],"each":[107],"following":[110],"steps":[111],"as:":[113],"reprocessing;":[116],"The":[123],"second":[124],"phase":[125],"be":[127],"classified":[128],"into":[129],"two,":[130],"i.e.,":[131],"extraction":[133],"extraction.":[136],"After":[137],"extract":[141],"useful":[142],"information":[143],"related":[144],"to":[145,150],"item's":[146],"use":[149],"rate":[151],"them":[152],"positive,":[154],"neutral,":[155],"or":[156],"negative.":[157]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
