{"id":"https://openalex.org/W4402982604","doi":"https://doi.org/10.1109/icme57554.2024.10688325","title":"How Does Textual Information Selection Influence Time Series Forecasting? A Cross-modal Perspective on Financial Volatility Prediction","display_name":"How Does Textual Information Selection Influence Time Series Forecasting? A Cross-modal Perspective on Financial Volatility Prediction","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4402982604","doi":"https://doi.org/10.1109/icme57554.2024.10688325"},"language":"en","primary_location":{"id":"doi:10.1109/icme57554.2024.10688325","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icme57554.2024.10688325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","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/A5001649087","display_name":"Hao Niu","orcid":"https://orcid.org/0000-0002-8327-8766"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Niu","raw_affiliation_strings":["Fudan University,Shanghai Key Laboratory of Data Science, School of Computer Science,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Fudan University,Shanghai Key Laboratory of Data Science, School of Computer Science,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001877137","display_name":"Yun Xiong","orcid":"https://orcid.org/0000-0002-8575-5415"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Xiong","raw_affiliation_strings":["Fudan University,Shanghai Key Laboratory of Data Science, School of Computer Science,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Fudan University,Shanghai Key Laboratory of Data Science, School of Computer Science,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037782710","display_name":"Xiaosu Wang","orcid":"https://orcid.org/0000-0002-8180-8604"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaosu Wang","raw_affiliation_strings":["Fudan University,Shanghai Key Laboratory of Data Science, School of Computer Science,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Fudan University,Shanghai Key Laboratory of Data Science, School of Computer Science,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085793821","display_name":"Biao Yang","orcid":"https://orcid.org/0000-0002-3630-1169"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Biao Yang","raw_affiliation_strings":["Fudan University,Shanghai Key Laboratory of Data Science, School of Computer Science,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Fudan University,Shanghai Key Laboratory of Data Science, School of Computer Science,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100447010","display_name":"Yao Zhang","orcid":"https://orcid.org/0000-0003-2789-6962"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhang","raw_affiliation_strings":["Fudan University,Shanghai Key Laboratory of Data Science, School of Computer Science,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Fudan University,Shanghai Key Laboratory of Data Science, School of Computer Science,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5001649087"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20693532,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","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"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","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/volatility","display_name":"Volatility (finance)","score":0.6877199411392212},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.6415219306945801},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5936617255210876},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5851740837097168},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5399724245071411},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5242010354995728},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.45110854506492615},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4488966763019562},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.4169090986251831},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.352605938911438},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2785508930683136},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.2631736993789673}],"concepts":[{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.6877199411392212},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.6415219306945801},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5936617255210876},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5851740837097168},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5399724245071411},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5242010354995728},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.45110854506492615},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4488966763019562},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.4169090986251831},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.352605938911438},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2785508930683136},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.2631736993789673},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/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/icme57554.2024.10688325","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icme57554.2024.10688325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337495","display_name":"Technology Development","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1919101720","https://openalex.org/W4205762803","https://openalex.org/W4390822878","https://openalex.org/W2291973775","https://openalex.org/W2535856026","https://openalex.org/W2265065644","https://openalex.org/W2379392295","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Real-world":[0],"time":[1,41,47,71,125,146],"series":[2,42,48,72,126,147],"are":[3],"often":[4],"accompanied":[5],"by":[6,119],"textual":[7,38,68,122,143],"descriptions":[8],"as":[9,49],"collateral":[10],"information,":[11],"especially":[12],"in":[13,74],"finance.":[14],"Financial":[15,57],"volatility":[16,76],"prediction":[17,77],"based":[18],"on":[19,33,40,70,132,145],"earnings":[20],"call":[21],"transcripts":[22],"is":[23],"such":[24],"a":[25,55,89,95],"typical":[26],"scenario.":[27,78],"Nevertheless,":[28],"current":[29],"studies":[30],"rarely":[31],"focus":[32],"the":[34,64,75,100,114,137],"cross-modal":[35],"impact":[36,65,141],"of":[37,66,142],"information":[39],"forecasting,":[43],"if":[44],"we":[45,53,82],"regard":[46],"another":[50],"modality.":[51],"Consequently,":[52],"propose":[54],"Denoised":[56],"Volatility":[58,96],"Prediction":[59],"(DeFVP)":[60],"model":[61],"to":[62,107],"investigate":[63],"varying":[67],"selection":[69,144],"forecasting":[73],"To":[79],"this":[80],"end,":[81],"jointly":[83],"train":[84],"two":[85],"neural":[86],"network":[87],"modules:":[88],"Differentiable":[90],"Binary":[91],"Selector":[92],"(DBS)":[93],"and":[94,139],"Predictor":[97],"(VP).":[98],"Firstly,":[99],"DBS":[101],"module":[102,116],"assigns":[103],"learnable":[104],"Bernoulli":[105],"variables":[106],"sentences":[108],"for":[109],"identifying":[110],"helpful":[111],"sentences.":[112],"Next,":[113],"VP":[115],"makes":[117],"predictions":[118],"imposing":[120],"selected":[121],"influence":[123],"into":[124],"modeling.":[127],"We":[128],"conduct":[129],"extensive":[130],"experiments":[131],"three":[133],"real-world":[134],"datasets,":[135],"demonstrating":[136],"significant":[138],"synergistic":[140],"forecasting.":[148],"<sup":[149],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[150],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>":[151]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
