{"id":"https://openalex.org/W4392909334","doi":"https://doi.org/10.1109/icassp48485.2024.10447824","title":"MTRGL: Effective Temporal Correlation Discerning Through Multi-Modal Temporal Relational Graph Learning","display_name":"MTRGL: Effective Temporal Correlation Discerning Through Multi-Modal Temporal Relational Graph Learning","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392909334","doi":"https://doi.org/10.1109/icassp48485.2024.10447824"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10447824","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10447824","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5023571218","display_name":"Junwei Su","orcid":"https://orcid.org/0000-0001-7154-8928"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Junwei Su","raw_affiliation_strings":["The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109137544","display_name":"Shangong Wu","orcid":"https://orcid.org/0000-0003-2677-9289"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Wu","raw_affiliation_strings":["Hefei University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hefei University of Technology","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100325434","display_name":"Jinhui Li","orcid":null},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jinhui Li","raw_affiliation_strings":["The University of Toronto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Toronto","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3055,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.60022162,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"6025","last_page":"6029"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.8575000166893005,"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/T10028","display_name":"Topic Modeling","score":0.8575000166893005,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.7418000102043152,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13401","display_name":"Social and Cultural Studies","score":0.70169997215271,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social 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":0.7065755128860474},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.6502761840820312},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5357024073600769},{"id":"https://openalex.org/keywords/statistical-relational-learning","display_name":"Statistical relational learning","score":0.49274876713752747},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.42465150356292725},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4126013517379761},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33659827709198},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.18863233923912048},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.14803165197372437},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14227762818336487},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.05161064863204956}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7065755128860474},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.6502761840820312},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5357024073600769},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.49274876713752747},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.42465150356292725},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4126013517379761},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33659827709198},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.18863233923912048},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.14803165197372437},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14227762818336487},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.05161064863204956},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp48485.2024.10447824","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10447824","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.5,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G6146042157","display_name":null,"funder_award_id":"2022CSJGG1200","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G800000706","display_name":null,"funder_award_id":"42302326","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320307110","display_name":"Delta","ror":"https://ror.org/03g9c1e75"},{"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":27,"referenced_works":["https://openalex.org/W2157331557","https://openalex.org/W2553285716","https://openalex.org/W2598525681","https://openalex.org/W2885150722","https://openalex.org/W2965683718","https://openalex.org/W3007404067","https://openalex.org/W3021475001","https://openalex.org/W3022746105","https://openalex.org/W3116042400","https://openalex.org/W3122010751","https://openalex.org/W3135013702","https://openalex.org/W3144701084","https://openalex.org/W3157999218","https://openalex.org/W3173128495","https://openalex.org/W4283784923","https://openalex.org/W4286750969","https://openalex.org/W4287755062","https://openalex.org/W4288436642","https://openalex.org/W4323848232","https://openalex.org/W4364320763","https://openalex.org/W4367046696","https://openalex.org/W4367368990","https://openalex.org/W4378881184","https://openalex.org/W6729621075","https://openalex.org/W6779860234","https://openalex.org/W6840581513","https://openalex.org/W6862281582"],"related_works":["https://openalex.org/W168012431","https://openalex.org/W4285191285","https://openalex.org/W1987457987","https://openalex.org/W1605272418","https://openalex.org/W2320781667","https://openalex.org/W2734531055","https://openalex.org/W1521211580","https://openalex.org/W2793712294","https://openalex.org/W1558526662","https://openalex.org/W4226145644"],"abstract_inverted_index":{"In":[0],"this":[1],"study,":[2],"we":[3,54],"explore":[4],"the":[5,46,109],"synergy":[6],"of":[7,48,112],"deep":[8],"learning":[9],"and":[10,26,70,77],"financial":[11],"market":[12],"applications,":[13],"focusing":[14],"on":[15,105],"pair":[16,37,120],"trading.":[17],"This":[18,85],"market-neutral":[19],"strategy":[20],"is":[21,27,39],"integral":[22],"to":[23],"quantitative":[24],"finance":[25],"apt":[28],"for":[29],"advanced":[30],"deep-learning":[31],"techniques.":[32],"A":[33],"pivotal":[34],"challenge":[35],"in":[36,117],"trading":[38,121],"discerning":[40],"temporal":[41,75,81,88,93],"correlations":[42],"among":[43],"entities,":[44],"necessitating":[45],"integration":[47],"diverse":[49],"data":[50,69],"modalities.":[51],"Addressing":[52],"this,":[53],"introduce":[55],"a":[56,74,79,92],"novel":[57],"framework,":[58],"Multi-modal":[59],"Temporal":[60],"Relation":[61],"Graph":[62],"Learning":[63],"(MTRGL).":[64],"MTRGL":[65],"combines":[66],"time":[67],"series":[68],"discrete":[71],"features":[72],"into":[73],"graph":[76,82,94],"employs":[78],"memory-based":[80],"neural":[83],"network.":[84],"approach":[86],"reframes":[87],"correlation":[89],"identification":[90],"as":[91],"link":[95],"prediction":[96],"task,":[97],"which":[98],"has":[99],"shown":[100],"empirical":[101],"success.":[102],"Our":[103],"experiments":[104],"real-world":[106],"datasets":[107],"confirm":[108],"superior":[110],"performance":[111],"MTRGL,":[113],"emphasizing":[114],"its":[115],"promise":[116],"refining":[118],"automated":[119],"strategies.":[122]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
