{"id":"https://openalex.org/W2890354514","doi":"https://doi.org/10.1109/access.2018.2869735","title":"Stock Market Prediction via Multi-Source Multiple Instance Learning","display_name":"Stock Market Prediction via Multi-Source Multiple Instance Learning","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2890354514","doi":"https://doi.org/10.1109/access.2018.2869735","mag":"2890354514"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2869735","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2869735","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2869735","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100672722","display_name":"Xi Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xi Zhang","raw_affiliation_strings":["Key Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078052542","display_name":"Siyu Qu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siyu Qu","raw_affiliation_strings":["Key Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006604874","display_name":"Jieyun Huang","orcid":"https://orcid.org/0000-0001-9569-4962"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jieyun Huang","raw_affiliation_strings":["Key Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113587199","display_name":"Binxing Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binxing Fang","raw_affiliation_strings":["Key Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036357902","display_name":"Philip S. Yu","orcid":"https://orcid.org/0000-0002-3491-5968"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip Yu","raw_affiliation_strings":["Department of Computer Science, The University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100672722"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":13.6463,"has_fulltext":false,"cited_by_count":147,"citation_normalized_percentile":{"value":0.98922932,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"50720","last_page":"50728"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9991000294685364,"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":0.9991000294685364,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9987000226974487,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.818516731262207},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7143982648849487},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.6660754680633545},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5203877687454224},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48739320039749146},{"id":"https://openalex.org/keywords/data-source","display_name":"Data source","score":0.47689464688301086},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.4481363892555237},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42716264724731445},{"id":"https://openalex.org/keywords/stock-market-prediction","display_name":"Stock market prediction","score":0.4123515188694}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.818516731262207},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7143982648849487},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.6660754680633545},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5203877687454224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48739320039749146},{"id":"https://openalex.org/C2983685735","wikidata":"https://www.wikidata.org/wiki/Q5227355","display_name":"Data source","level":2,"score":0.47689464688301086},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.4481363892555237},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42716264724731445},{"id":"https://openalex.org/C2776256503","wikidata":"https://www.wikidata.org/wiki/Q7617906","display_name":"Stock market prediction","level":4,"score":0.4123515188694},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2869735","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2869735","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:728d478dc48948e097f7c98555e47e5a","is_oa":true,"landing_page_url":"https://doaj.org/article/728d478dc48948e097f7c98555e47e5a","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 50720-50728 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2869735","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2869735","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3218167762","display_name":null,"funder_award_id":"IIS-1526499","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4593569228","display_name":null,"funder_award_id":"61300014","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5798848519","display_name":null,"funder_award_id":"IIS-1763325","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7398055925","display_name":null,"funder_award_id":"CNS-1626432","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W876282063","https://openalex.org/W1983381518","https://openalex.org/W2010792435","https://openalex.org/W2043009158","https://openalex.org/W2048658075","https://openalex.org/W2066381742","https://openalex.org/W2067624665","https://openalex.org/W2070013029","https://openalex.org/W2090637028","https://openalex.org/W2100495367","https://openalex.org/W2110119381","https://openalex.org/W2115672776","https://openalex.org/W2116209939","https://openalex.org/W2126267628","https://openalex.org/W2128310653","https://openalex.org/W2129604374","https://openalex.org/W2131744502","https://openalex.org/W2165800793","https://openalex.org/W2167187514","https://openalex.org/W2171468534","https://openalex.org/W2171683557","https://openalex.org/W2250629460","https://openalex.org/W2250886571","https://openalex.org/W2251709641","https://openalex.org/W2283304333","https://openalex.org/W2296438605","https://openalex.org/W2405188152","https://openalex.org/W2510046892","https://openalex.org/W2605021547","https://openalex.org/W3105472840","https://openalex.org/W4247977950","https://openalex.org/W6623742358","https://openalex.org/W6676914691","https://openalex.org/W6677467840","https://openalex.org/W6679108089","https://openalex.org/W6679775712","https://openalex.org/W6684350123","https://openalex.org/W6684439670","https://openalex.org/W6691199604","https://openalex.org/W6691510579","https://openalex.org/W6691655829","https://openalex.org/W6697136110","https://openalex.org/W6713376747","https://openalex.org/W6736095516","https://openalex.org/W6785674019"],"related_works":["https://openalex.org/W2586556113","https://openalex.org/W2370669686","https://openalex.org/W3135178882","https://openalex.org/W2542516223","https://openalex.org/W2624043242","https://openalex.org/W18886619","https://openalex.org/W2110351804","https://openalex.org/W3023530306","https://openalex.org/W2086993069","https://openalex.org/W3209908847"],"abstract_inverted_index":{"Forecasting":[0],"the":[1,12,23,28,32,35,55,60,69,79,101,111,126,129,135,149,157,166,169],"stock":[2,61,72],"market":[3,62,73],"movements":[4],"is":[5,144,162],"an":[6],"important":[7],"and":[8,25,49,85,121,132,155],"challenging":[9],"task.":[10],"As":[11],"Web":[13,29],"information":[14,160],"grows,":[15],"researchers":[16],"begin":[17],"to":[18,30,67,146,164],"extract":[19],"effective":[20],"indicators":[21,36],"(e.g.,":[22],"events":[24],"sentiments)":[26],"from":[27,128],"facilitate":[31],"prediction.":[33],"However,":[34],"obtained":[37],"in":[38],"previous":[39],"studies":[40],"are":[41],"usually":[42],"based":[43],"on":[44,125],"only":[45],"one":[46],"data":[47,83,103,127,153],"source":[48,154],"thus":[50],"may":[51],"not":[52],"fully":[53],"cover":[54],"factors":[56],"that":[57,92,161],"can":[58,93],"affect":[59],"movements.":[63],"In":[64,140],"this":[65],"paper,":[66],"improve":[68],"prediction":[70],"for":[71],"composite":[74],"index":[75],"movements,":[76,167],"we":[77,114],"exploit":[78],"consistencies":[80],"among":[81],"different":[82],"sources,":[84],"develop":[86],"a":[87,105,117],"multi-source":[88],"multiple":[89],"instance":[90],"model":[91],"effectively":[94,109],"combine":[95],"events,":[96,113],"sentiments,":[97],"as":[98,100],"well":[99],"quantitative":[102],"into":[104],"comprehensive":[106],"framework.":[107],"To":[108],"capture":[110],"news":[112],"successfully":[115],"apply":[116],"novel":[118],"event":[119],"extraction":[120],"representation":[122],"method.":[123],"Evaluations":[124],"year":[130],"2015":[131],"2016":[133],"demonstrate":[134],"effectiveness":[136],"of":[137,151],"our":[138,142],"model.":[139],"addition,":[141],"approach":[143],"able":[145],"automatically":[147],"determine":[148],"importance":[150],"each":[152],"identify":[156],"crucial":[158],"input":[159],"considered":[163],"drive":[165],"making":[168],"predictions":[170],"interpretable.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":25},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":25},{"year":2020,"cited_by_count":20},{"year":2019,"cited_by_count":16},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
