{"id":"https://openalex.org/W2902276438","doi":"https://doi.org/10.1109/icacci.2018.8554424","title":"An Ensemble Stock Predictor and Recommender System","display_name":"An Ensemble Stock Predictor and Recommender System","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2902276438","doi":"https://doi.org/10.1109/icacci.2018.8554424","mag":"2902276438"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2018.8554424","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2018.8554424","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5048775914","display_name":"M Sannidhi D Hegde","orcid":null},"institutions":[{"id":"https://openalex.org/I196608512","display_name":"PES University","ror":"https://ror.org/05m169e78","country_code":"IN","type":"education","lineage":["https://openalex.org/I196608512"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Manoj S Hegde","raw_affiliation_strings":["Computer Science and Engineering, PES University, Bangalore"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, PES University, Bangalore","institution_ids":["https://openalex.org/I196608512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016272714","display_name":"G. Bala Krishna","orcid":null},"institutions":[{"id":"https://openalex.org/I196608512","display_name":"PES University","ror":"https://ror.org/05m169e78","country_code":"IN","type":"education","lineage":["https://openalex.org/I196608512"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ganesh Krishna","raw_affiliation_strings":["Computer Science and Engineering, PES University, Bangalore"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, PES University, Bangalore","institution_ids":["https://openalex.org/I196608512"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015522054","display_name":"Ramamoorthy Srinath","orcid":"https://orcid.org/0000-0003-1818-8577"},"institutions":[{"id":"https://openalex.org/I196608512","display_name":"PES University","ror":"https://ror.org/05m169e78","country_code":"IN","type":"education","lineage":["https://openalex.org/I196608512"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ramamoorthy Srinath","raw_affiliation_strings":["Computer Science and Engineering, PES University, Bangalore"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, PES University, Bangalore","institution_ids":["https://openalex.org/I196608512"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048775914"],"corresponding_institution_ids":["https://openalex.org/I196608512"],"apc_list":null,"apc_paid":null,"fwci":2.9645,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.91616556,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1981","last_page":"1985"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9828000068664551,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.6971046924591064},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6088409423828125},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.5429049134254456},{"id":"https://openalex.org/keywords/stock-exchange","display_name":"Stock exchange","score":0.524795413017273},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5172513127326965},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.48526641726493835},{"id":"https://openalex.org/keywords/stock-market-prediction","display_name":"Stock market prediction","score":0.42922770977020264},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4215160012245178},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4182557463645935},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4111817479133606},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3333466053009033},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.22887343168258667},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.2090614140033722},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.17306041717529297},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08376333117485046}],"concepts":[{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.6971046924591064},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6088409423828125},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.5429049134254456},{"id":"https://openalex.org/C200870193","wikidata":"https://www.wikidata.org/wiki/Q11691","display_name":"Stock exchange","level":2,"score":0.524795413017273},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5172513127326965},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.48526641726493835},{"id":"https://openalex.org/C2776256503","wikidata":"https://www.wikidata.org/wiki/Q7617906","display_name":"Stock market prediction","level":4,"score":0.42922770977020264},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4215160012245178},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4182557463645935},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4111817479133606},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3333466053009033},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.22887343168258667},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.2090614140033722},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.17306041717529297},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08376333117485046},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icacci.2018.8554424","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2018.8554424","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2085960120","https://openalex.org/W2182617889","https://openalex.org/W2734986640","https://openalex.org/W2741051040","https://openalex.org/W2773831388","https://openalex.org/W2774513877","https://openalex.org/W2783813266","https://openalex.org/W2799024472","https://openalex.org/W2799178524","https://openalex.org/W6686054988","https://openalex.org/W6742049128"],"related_works":["https://openalex.org/W2586556113","https://openalex.org/W3135178882","https://openalex.org/W2542516223","https://openalex.org/W2624043242","https://openalex.org/W3209908847","https://openalex.org/W3023530306","https://openalex.org/W2110351804","https://openalex.org/W1980850818","https://openalex.org/W2785399422","https://openalex.org/W3011320813"],"abstract_inverted_index":{"Stock":[0,89],"market":[1,37],"analysis":[2],"and":[3,16,28,53,62,103,110,166],"prediction":[4],"tools":[5],"have":[6],"been":[7],"prevalent":[8],"for":[9,71,116],"several":[10],"years":[11],"now":[12],"with":[13,122,128,187],"various":[14,60],"techniques":[15],"models":[17],"to":[18,34,68,108,130,150,173,178,202],"predict":[19,35,111],"stock":[20,36,50,57,82,114,136,170,189,210],"markets":[21],"efficiently.":[22],"This":[23],"paper":[24],"presents":[25],"the":[26,56,112,134,169,198,209],"design":[27],"implementation":[29],"of":[30,59,119,124],"a":[31,72,93,117,139,144,151,181,192],"novel":[32],"technique":[33],"trends.":[38,211],"The":[39,75,96,157],"approach":[40],"is":[41,77,141,148,159],"an":[42],"ensemble":[43],"model":[44,76,97,199],"which":[45,66,147],"takes":[46],"into":[47,143],"account":[48],"historical":[49,81],"data,":[51],"tweets":[52],"news":[54],"affecting":[55],"prices":[58,190],"companies":[61,121],"provides":[63],"recommendations":[64,175],"on":[65,79,161,176],"stocks":[67],"invest":[69,179],"in":[70,180,207],"particular":[73,182],"duration.":[74],"built":[78],"real":[80,188],"data":[83],"set":[84],"obtained":[85],"from":[86],"Indian":[87,131],"National":[88],"Exchange":[90],"(www.nseindia.com)":[91],"over":[92,191],"20-year":[94],"period.":[95],"uses":[98],"Recurrent":[99],"Neural":[100,153],"Networks":[101],"(RNN)":[102],"Long-Short":[104],"Term":[105],"Memory":[106],"(LSTM)":[107],"learn":[109],"future":[113],"trend":[115,171],"basket":[118],"50":[120],"RMSE":[123],"1.43":[125],"(stock":[126],"units":[127],"respect":[129],"currency).":[132],"Finally,":[133],"predicted":[135],"price":[137],"within":[138,168],"duration":[140],"converted":[142],"graphical":[145],"image,":[146,172],"passed":[149],"Convolutional":[152],"Network":[154],"(CNN)":[155],"classifier.":[156],"classifier":[158],"trained":[160],"finer":[162],"features":[163],"like":[164],"peaks":[165],"troughs":[167],"provide":[174],"when":[177],"company":[183],"stock.":[184],"When":[185],"tested":[186],"week,":[193],"it":[194],"was":[195,200],"found":[196],"that":[197],"able":[201],"achieve":[203],"extremely":[204],"high":[205],"accuracy":[206],"predicting":[208]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}