{"id":"https://openalex.org/W2127805495","doi":"https://doi.org/10.1109/cifer.2011.5953571","title":"A fuzzy model of a European index based on automatically extracted content information","display_name":"A fuzzy model of a European index based on automatically extracted content information","publication_year":2011,"publication_date":"2011-04-01","ids":{"openalex":"https://openalex.org/W2127805495","doi":"https://doi.org/10.1109/cifer.2011.5953571","mag":"2127805495"},"language":"en","primary_location":{"id":"doi:10.1109/cifer.2011.5953571","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cifer.2011.5953571","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr)","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/A5078530193","display_name":"Viorel Milea","orcid":"https://orcid.org/0000-0002-3203-514X"},"institutions":[{"id":"https://openalex.org/I913958620","display_name":"Erasmus University Rotterdam","ror":"https://ror.org/057w15z03","country_code":"NL","type":"education","lineage":["https://openalex.org/I913958620"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Viorel Milea","raw_affiliation_strings":["Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, Netherlands","institution_ids":["https://openalex.org/I913958620"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087774814","display_name":"Rui Almeida","orcid":"https://orcid.org/0000-0002-7844-0167"},"institutions":[{"id":"https://openalex.org/I913958620","display_name":"Erasmus University Rotterdam","ror":"https://ror.org/057w15z03","country_code":"NL","type":"education","lineage":["https://openalex.org/I913958620"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Rui J. Almeida","raw_affiliation_strings":["Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, Netherlands","institution_ids":["https://openalex.org/I913958620"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080242338","display_name":"Uzay Kaymak","orcid":"https://orcid.org/0000-0002-4500-9098"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]},{"id":"https://openalex.org/I913958620","display_name":"Erasmus University Rotterdam","ror":"https://ror.org/057w15z03","country_code":"NL","type":"education","lineage":["https://openalex.org/I913958620"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Uzay Kaymak","raw_affiliation_strings":["Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, Netherlands","Industrial Engineering Department, Technical University Eindhoven, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, Netherlands","institution_ids":["https://openalex.org/I913958620"]},{"raw_affiliation_string":"Industrial Engineering Department, Technical University Eindhoven, Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044867921","display_name":"Flavius Fr\u0103sincar","orcid":"https://orcid.org/0000-0002-8031-758X"},"institutions":[{"id":"https://openalex.org/I913958620","display_name":"Erasmus University Rotterdam","ror":"https://ror.org/057w15z03","country_code":"NL","type":"education","lineage":["https://openalex.org/I913958620"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Flavius Frasincar","raw_affiliation_strings":["Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, Netherlands","institution_ids":["https://openalex.org/I913958620"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4314,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74143533,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9812999963760376,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9812999963760376,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9776999950408936,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.9431999921798706,"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/feature-selection","display_name":"Feature selection","score":0.7474878430366516},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7166543006896973},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6152513027191162},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5898979306221008},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5475531220436096},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.5343460440635681},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.518817126750946},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5147373676300049},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.5030269026756287},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4955497980117798},{"id":"https://openalex.org/keywords/content","display_name":"Content (measure theory)","score":0.4700896739959717},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.45866313576698303},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.43189701437950134},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4134621322154999},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4122990667819977},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.41024649143218994},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4067048132419586},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1363157331943512},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13284221291542053},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09861156344413757}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7474878430366516},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7166543006896973},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6152513027191162},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5898979306221008},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5475531220436096},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.5343460440635681},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.518817126750946},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5147373676300049},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.5030269026756287},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4955497980117798},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.4700896739959717},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.45866313576698303},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.43189701437950134},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4134621322154999},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4122990667819977},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.41024649143218994},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4067048132419586},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1363157331943512},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13284221291542053},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09861156344413757},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/cifer.2011.5953571","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cifer.2011.5953571","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.tue.nl:publications/5c245b5a-138c-4069-8ba5-5309acc9707a","is_oa":false,"landing_page_url":"https://research.tue.nl/en/publications/5c245b5a-138c-4069-8ba5-5309acc9707a","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Milea, D V, Almeida, R J, Kaymak, U & Frasincar, F 2011, A fuzzy model of a European index based on automatically extracted content information. in Proceedings of the 2011 IEEE Symposium on Computational Intelligence for Financial Engineering & Economics (CIFEr 2011), April 11-15, 2011, Paris, France. Institute of Electrical and Electronics Engineers, Piscataway, USA, pp. 140-147, conference; 2011 IEEE Symposium on Computational Intelligence for Financial Engineering & Economics (CIFEr 2011); 2011-04-11; 2011-04-15, 11/04/11. https://doi.org/10.1109/CIFER.2011.5953571","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:eur:oai:pure.eur.nl:publications/d0c8498d-de7b-4bb7-8c16-54855a4262ab","is_oa":false,"landing_page_url":"https://pure.eur.nl/en/publications/d0c8498d-de7b-4bb7-8c16-54855a4262ab","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2011 IEEE Symposium on Computational Intelligence for Financial Engineering &amp; Economics (CIFeEr 2011)","raw_type":"info:eu-repo/semantics/conferencepaper"},{"id":"pmh:oai:pure.eur.nl:publications/d0c8498d-de7b-4bb7-8c16-54855a4262ab","is_oa":false,"landing_page_url":"http://hdl.handle.net/1765/31235","pdf_url":null,"source":{"id":"https://openalex.org/S4306401266","display_name":"EUR Research Repository (Erasmus University Rotterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I913958620","host_organization_name":"Erasmus University Rotterdam","host_organization_lineage":["https://openalex.org/I913958620"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Milea, V, Almeida e Santos Nogueira, R, Kaymak, U & Frasincar, F 2011, A Fuzzy Model of a European Index Based on Automatically Extracted Content Information. in 2011 IEEE Symposium on Computational Intelligence for Financial Engineering & Economics (CIFeEr 2011). IEEE Computational Intelligence Society. https://doi.org/10.1109/CIFER.2011.5953571","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:tue:oai:pure.tue.nl:publications/5c245b5a-138c-4069-8ba5-5309acc9707a","is_oa":false,"landing_page_url":"https://research.tue.nl/nl/publications/5c245b5a-138c-4069-8ba5-5309acc9707a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the 2011 IEEE Symposium on Computational Intelligence for Financial Engineering &amp; Economics (CIFEr 2011), April 11-15, 2011, Paris, France, 140 - 147","raw_type":"info:eu-repo/semantics/conferencepaper"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.49000000953674316,"display_name":"Partnerships for the goals"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320301","display_name":"European Science Foundation","ror":"https://ror.org/04esata81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W47512413","https://openalex.org/W145806832","https://openalex.org/W1256013790","https://openalex.org/W1560688497","https://openalex.org/W1853840354","https://openalex.org/W1948020393","https://openalex.org/W1976034104","https://openalex.org/W1977994906","https://openalex.org/W1996430422","https://openalex.org/W2003458432","https://openalex.org/W2071309675","https://openalex.org/W2079325629","https://openalex.org/W2102041666","https://openalex.org/W2103495943","https://openalex.org/W2113076747","https://openalex.org/W2120881933","https://openalex.org/W2129777964","https://openalex.org/W2135198734","https://openalex.org/W2145479133","https://openalex.org/W2146047893","https://openalex.org/W2998216295","https://openalex.org/W3122944446","https://openalex.org/W4211012857","https://openalex.org/W4233391551","https://openalex.org/W4285719527","https://openalex.org/W6601896568","https://openalex.org/W6605892302","https://openalex.org/W6628215450","https://openalex.org/W6675672671","https://openalex.org/W7066667914"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W1531601525","https://openalex.org/W2396366225","https://openalex.org/W2384344231"],"abstract_inverted_index":{"In":[0],"this":[1,38],"paper":[2],"we":[3,40,87],"build":[4],"on":[5,16,25,42,93,99,109,117],"previous":[6],"work":[7],"related":[8],"to":[9],"predicting":[10],"the":[11,27,71,75,79,94,110],"MSCI":[12],"EURO":[13],"index":[14],"based":[15],"content":[17,63],"analysis":[18],"of":[19,29,58,74,81,91,113],"ECB":[20],"statements.":[21],"Our":[22],"focus":[23],"is":[24],"reducing":[26,78],"number":[28,80],"features":[30,60,82],"employed":[31],"for":[32],"prediction":[33],"through":[34],"feature":[35,51],"selection.":[36,53],"For":[37],"purpose":[39],"rely":[41],"two":[43],"methodologies:":[44],"(stepwise)":[45],"linear":[46,85],"regression":[47,86],"and":[48],"greedy":[49,103],"forward":[50,104],"subset":[52],"The":[54],"original":[55],"dataset":[56],"consists":[57],"13":[59],"(General":[61],"Inquirer":[62],"categories).":[64],"Both":[65],"methodologies":[66],"provide":[67],"an":[68,89,107],"improvement":[69],"in":[70],"overall":[72],"accuracy":[73,90,108],"model,":[76],"while":[77,102,115],"employed.":[83],"Through":[84],"achieve":[88],"67.58%":[92],"testing":[95],"set":[96,112],"by":[97],"relying":[98,116],"six":[100],"features,":[101],"selection":[105],"enables":[106],"test":[111],"69.50%":[114],"eight":[118],"features.":[119]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
