{"id":"https://openalex.org/W2974780824","doi":"https://doi.org/10.1109/ic3.2019.8844895","title":"Enhancing Text Mining Using Deep Learning Models","display_name":"Enhancing Text Mining Using Deep Learning Models","publication_year":2019,"publication_date":"2019-08-01","ids":{"openalex":"https://openalex.org/W2974780824","doi":"https://doi.org/10.1109/ic3.2019.8844895","mag":"2974780824"},"language":"en","primary_location":{"id":"doi:10.1109/ic3.2019.8844895","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic3.2019.8844895","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Twelfth International Conference on Contemporary Computing (IC3)","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/A5101582854","display_name":"Avinash Chandra Pandey","orcid":"https://orcid.org/0000-0002-0487-6742"},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Avinash Chandra Pandey","raw_affiliation_strings":["Jaypee Institute of Information Technology, Noida"],"affiliations":[{"raw_affiliation_string":"Jaypee Institute of Information Technology, Noida","institution_ids":["https://openalex.org/I154970844"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053157945","display_name":"Mukund Garg","orcid":null},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mukund Garg","raw_affiliation_strings":["Jaypee Institute of Information Technology, Noida"],"affiliations":[{"raw_affiliation_string":"Jaypee Institute of Information Technology, Noida","institution_ids":["https://openalex.org/I154970844"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036444865","display_name":"Sonali Rajput","orcid":null},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sonali Rajput","raw_affiliation_strings":["Jaypee Institute of Information Technology, Noida"],"affiliations":[{"raw_affiliation_string":"Jaypee Institute of Information Technology, Noida","institution_ids":["https://openalex.org/I154970844"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101582854"],"corresponding_institution_ids":["https://openalex.org/I154970844"],"apc_list":null,"apc_paid":null,"fwci":1.1201,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.84009348,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9980999827384949,"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":0.9980999827384949,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9976999759674072,"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":0.9957000017166138,"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":0.7741999626159668},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6385157108306885},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6372100114822388},{"id":"https://openalex.org/keywords/heap","display_name":"Heap (data structure)","score":0.529646635055542},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.520770251750946},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4470217823982239},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4137188792228699},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41369134187698364},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36119332909584045}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7741999626159668},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6385157108306885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6372100114822388},{"id":"https://openalex.org/C134757568","wikidata":"https://www.wikidata.org/wiki/Q274089","display_name":"Heap (data structure)","level":2,"score":0.529646635055542},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.520770251750946},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4470217823982239},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4137188792228699},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41369134187698364},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36119332909584045},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ic3.2019.8844895","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic3.2019.8844895","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Twelfth International Conference on Contemporary Computing (IC3)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2296034778","https://openalex.org/W2413904250","https://openalex.org/W2550999023","https://openalex.org/W2552192644","https://openalex.org/W2558287987","https://openalex.org/W2571563030","https://openalex.org/W2573310807","https://openalex.org/W2576516426","https://openalex.org/W2587019100","https://openalex.org/W2594056497","https://openalex.org/W2605058246","https://openalex.org/W2758340275","https://openalex.org/W2760392765","https://openalex.org/W2770260627","https://openalex.org/W2773861051","https://openalex.org/W2781850624","https://openalex.org/W2788347302","https://openalex.org/W2791980930","https://openalex.org/W2804552911","https://openalex.org/W2812053664","https://openalex.org/W2888021909","https://openalex.org/W2900625152","https://openalex.org/W2913553601","https://openalex.org/W2925724022","https://openalex.org/W2962739339","https://openalex.org/W2964045325","https://openalex.org/W2964236337","https://openalex.org/W3147675069","https://openalex.org/W4252078918","https://openalex.org/W6732001033","https://openalex.org/W6732308929"],"related_works":["https://openalex.org/W3158777280","https://openalex.org/W2093687902","https://openalex.org/W2949158926","https://openalex.org/W4301885003","https://openalex.org/W2005058894","https://openalex.org/W1996981508","https://openalex.org/W1989205740","https://openalex.org/W4387561287","https://openalex.org/W3008584592","https://openalex.org/W4380075502"],"abstract_inverted_index":{"Text":[0],"mining,":[1],"a":[2,175],"section":[3],"of":[4,14,30,48,75,90,116,118,157,192],"the":[5,15,28,42,56,71,76,88,114,123,138,145,166,190],"synthetic":[6],"intelligence,":[7],"is":[8,59],"gaining":[9,34],"grounds":[10],"nowadays":[11],"in":[12,17,33,40,46,134],"terms":[13,47],"applications":[16],"business":[18],"and":[19,23,39,50,66,99,141,148,155,169],"analysis.":[20],"Varied":[21],"sectors":[22],"domains":[24],"across":[25],"industries":[26],"understand":[27],"potential":[29],"text":[31,63],"mining":[32,36,64],"information,":[35],"helpful":[37],"data":[38],"enhancing":[41],"choice":[43],"creating":[44],"method":[45],"speed":[49],"potency.":[51],"In":[52],"today's":[53],"world,":[54],"where":[55],"web":[57],"area":[58],"overflowing":[60],"with":[61],"data,":[62],"technology":[65],"solutions":[67],"will":[68],"persuade":[69],"be":[70],"turning":[72],"purpose.":[73],"Most":[74],"recent":[77],"researches":[78],"conducted":[79],"during":[80],"this":[81],"space":[82],"focused":[83],"principally":[84],"on":[85,103],"advanced":[86],"or":[87],"hybrid":[89],"deep":[91,128],"neural":[92],"networks":[93],"so":[94],"as":[95],"to":[96,121,136],"induce":[97],"economical":[98],"higher":[100],"results.":[101],"Functioning":[102],"such":[104],"serious":[105],"models":[106,130,151,159],"isn't":[107],"solely":[108],"time":[109],"taking":[110],"however":[111],"conjointly":[112],"needs":[113],"usage":[115],"heap":[117],"resources.":[119],"Therefore,":[120],"get":[122],"comparable":[124],"results":[125],"only":[126],"basic":[127],"learning":[129,186],"have":[131,152,160],"been":[132,153,161,182],"used":[133,154],"order":[135],"minimize":[137],"model's":[139],"complexity":[140],"computational":[142],"cost.":[143],"For":[144],"same,":[146],"RNN":[147,193],"LSTM":[149,195],"based":[150,196],"accuracy":[156],"proposed":[158],"enhanced":[162],"by":[163,164],"varying":[165],"hyper":[167],"parameters":[168],"using":[170,184],"Glove":[171],"word":[172],"embeddings.":[173],"Moreover,":[174],"labeled":[176],"dataset":[177],"named":[178],"Sentiment5k":[179],"has":[180],"also":[181],"created":[183],"semi-supervised":[185],"approach":[187],"for":[188],"evaluating":[189],"performance":[191],"&":[194],"models.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}