{"id":"https://openalex.org/W3116340149","doi":"https://doi.org/10.1109/ictc49870.2020.9289258","title":"Forecasting Time-Series Trends by Merging Structured and Unstructured Datasets","display_name":"Forecasting Time-Series Trends by Merging Structured and Unstructured Datasets","publication_year":2020,"publication_date":"2020-10-21","ids":{"openalex":"https://openalex.org/W3116340149","doi":"https://doi.org/10.1109/ictc49870.2020.9289258","mag":"3116340149"},"language":"en","primary_location":{"id":"doi:10.1109/ictc49870.2020.9289258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc49870.2020.9289258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","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/A5110947250","display_name":"Ji Sang Park","orcid":null},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Ji Sang Park","raw_affiliation_strings":["Intelligent Robot Research Section, ETRI, Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Intelligent Robot Research Section, ETRI, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055703733","display_name":"Hyeon Sung Cho","orcid":"https://orcid.org/0000-0003-0029-6617"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyeon Sung Cho","raw_affiliation_strings":["Intelligent Robot Research Section, ETRI, Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Intelligent Robot Research Section, ETRI, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035547791","display_name":"Ji Sung Lee","orcid":"https://orcid.org/0000-0001-8194-3462"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ji Sung Lee","raw_affiliation_strings":["Intelligent Robot Research Section, ETRI, Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Intelligent Robot Research Section, ETRI, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048836052","display_name":"Kyoil Chung","orcid":null},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyo-Il Chung","raw_affiliation_strings":["Intelligent Robot Research Section, ETRI, Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Intelligent Robot Research Section, ETRI, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047330848","display_name":"Jeong\u2010Min Kim","orcid":"https://orcid.org/0000-0001-7213-5527"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeong Min Kim","raw_affiliation_strings":["Thinkpool Inc., Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Thinkpool Inc., Seoul, Republic of Korea","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108127294","display_name":"Dong Jin Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong Jin Kim","raw_affiliation_strings":["Thinkpool Inc., Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Thinkpool Inc., Seoul, Republic of Korea","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5110947250"],"corresponding_institution_ids":["https://openalex.org/I142401562"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22534751,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":null,"first_page":"1230","last_page":"1233"},"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9883999824523926,"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/computer-science","display_name":"Computer science","score":0.7855263948440552},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.6245020031929016},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5125272274017334},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5078292489051819},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4886517822742462},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.4708007574081421},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.46006619930267334},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45355162024497986},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4429395794868469},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40764909982681274}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7855263948440552},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.6245020031929016},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5125272274017334},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5078292489051819},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4886517822742462},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.4708007574081421},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.46006619930267334},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45355162024497986},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4429395794868469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40764909982681274},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictc49870.2020.9289258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc49870.2020.9289258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.5299999713897705}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2793864397","https://openalex.org/W2889482216","https://openalex.org/W2896551579","https://openalex.org/W2912036663","https://openalex.org/W2919148338","https://openalex.org/W2950843237","https://openalex.org/W2995741266","https://openalex.org/W2998298880","https://openalex.org/W4289373797","https://openalex.org/W4404049250","https://openalex.org/W6755455067","https://openalex.org/W6873698495"],"related_works":["https://openalex.org/W2120447654","https://openalex.org/W2977179488","https://openalex.org/W2144453115","https://openalex.org/W2128223750","https://openalex.org/W4238532390","https://openalex.org/W2188872161","https://openalex.org/W3193043704","https://openalex.org/W2961779879","https://openalex.org/W4386259002","https://openalex.org/W4372048956"],"abstract_inverted_index":{"This":[0,17],"paper":[1],"introduces":[2],"a":[3,66],"new":[4],"approach":[5],"to":[6,20],"forecast":[7],"daily":[8,44],"stock":[9,32,45,86,123],"trends":[10],"by":[11],"merging":[12,111],"structured":[13],"and":[14,89,95,132],"unstructured":[15],"datasets.":[16,105],"study":[18],"intends":[19],"reveal":[21],"the":[22,117],"effectiveness":[23],"of":[24,31,36,71],"using":[25,50,122],"supplemental":[26],"datasets":[27,114,125],"for":[28,85,102,129],"accurate":[29],"prediction":[30],"prices.":[33],"A":[34],"set":[35],"features,":[37],"which":[38],"is":[39],"seemingly":[40],"highly":[41],"correlated":[42],"with":[43],"price":[46],"variations,":[47],"are":[48,58,63,82,99,134],"selected":[49],"random":[51],"forest":[52],"optimization":[53],"technique.":[54],"Stock-relevant":[55],"keywords":[56],"that":[57,110],"extracted":[59],"from":[60,92],"news":[61,93],"articles":[62],"converted":[64],"into":[65],"time-series":[67],"dataset":[68],"in":[69],"terms":[70],"temporal":[72],"frequency.":[73],"Convolution":[74],"neural":[75],"network":[76],"(CNN)":[77],"based":[78],"deep":[79],"learning":[80],"models":[81,98],"generated":[83],"separately":[84],"trading":[87,124],"data":[88],"keyword":[90],"frequencies":[91],"articles,":[94],"two":[96,112],"CNN":[97],"merged":[100],"together":[101],"training":[103],"input":[104],"The":[106],"analysis":[107,131],"results":[108,120],"show":[109],"different":[113],"may":[115],"generate":[116],"better":[118],"forecasting":[119],"than":[121],"only.":[126],"Additional":[127],"issues":[128],"future":[130],"implementations":[133],"discussed.":[135]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
