{"id":"https://openalex.org/W3034948289","doi":"https://doi.org/10.24963/ijcai.2020/619","title":"F-HMTC: Detecting Financial Events for Investment Decisions Based on Neural Hierarchical Multi-Label Text Classification","display_name":"F-HMTC: Detecting Financial Events for Investment Decisions Based on Neural Hierarchical Multi-Label Text Classification","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3034948289","doi":"https://doi.org/10.24963/ijcai.2020/619","mag":"3034948289"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2020/619","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/619","pdf_url":"https://www.ijcai.org/proceedings/2020/0619.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2020/0619.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107386477","display_name":"Xin Liang","orcid":"https://orcid.org/0000-0002-4577-0119"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Liang","raw_affiliation_strings":["School of Data Science and Engineering, East China Normal University, Shanghai, China","Shanghai Engineering Research Center on Big Data Management System, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science and Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]},{"raw_affiliation_string":"Shanghai Engineering Research Center on Big Data Management System, Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069869295","display_name":"Dawei Cheng","orcid":"https://orcid.org/0000-0002-5877-7387"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dawei Cheng","raw_affiliation_strings":["Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China","Seekdata Inc., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Seekdata Inc., Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103021848","display_name":"Fangzhou Yang","orcid":"https://orcid.org/0009-0001-7293-4975"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fangzhou Yang","raw_affiliation_strings":["Seekdata Inc., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seekdata Inc., Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102883111","display_name":"Yifeng Luo","orcid":"https://orcid.org/0000-0003-4863-3432"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifeng Luo","raw_affiliation_strings":["School of Data Science and Engineering, East China Normal University, Shanghai, China","Shanghai Engineering Research Center on Big Data Management System, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science and Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]},{"raw_affiliation_string":"Shanghai Engineering Research Center on Big Data Management System, Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089931216","display_name":"Weining Qian","orcid":"https://orcid.org/0000-0002-4132-8630"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weining Qian","raw_affiliation_strings":["School of Data Science and Engineering, East China Normal University, Shanghai, China","Shanghai Engineering Research Center on Big Data Management System, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science and Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]},{"raw_affiliation_string":"Shanghai Engineering Research Center on Big Data Management System, Shanghai, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101511862","display_name":"Aoying Zhou","orcid":"https://orcid.org/0000-0002-4665-7302"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aoying Zhou","raw_affiliation_strings":["School of Data Science and Engineering, East China Normal University, Shanghai, China","Shanghai Engineering Research Center on Big Data Management System, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science and Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]},{"raw_affiliation_string":"Shanghai Engineering Research Center on Big Data Management System, Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.6476,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.95047809,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4490","last_page":"4496"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9948999881744385,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.994700014591217,"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/computer-science","display_name":"Computer science","score":0.6882591247558594},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.6375750303268433},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5909680128097534},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.5378972291946411},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5218763947486877},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4736156165599823},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4425238072872162},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4208373725414276},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4137556552886963},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09033408761024475}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6882591247558594},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.6375750303268433},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5909680128097534},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.5378972291946411},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5218763947486877},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4736156165599823},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4425238072872162},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4208373725414276},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4137556552886963},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09033408761024475},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2020/619","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/619","pdf_url":"https://www.ijcai.org/proceedings/2020/0619.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2020/619","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/619","pdf_url":"https://www.ijcai.org/proceedings/2020/0619.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322370","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3034948289.pdf","grobid_xml":"https://content.openalex.org/works/W3034948289.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W85880394","https://openalex.org/W1550206324","https://openalex.org/W1614298861","https://openalex.org/W1826790618","https://openalex.org/W1832693441","https://openalex.org/W1880262756","https://openalex.org/W2014566476","https://openalex.org/W2117225622","https://openalex.org/W2137165876","https://openalex.org/W2149684865","https://openalex.org/W2407776548","https://openalex.org/W2443284789","https://openalex.org/W2470673105","https://openalex.org/W2788667846","https://openalex.org/W2798754355","https://openalex.org/W2896457183","https://openalex.org/W2963626623","https://openalex.org/W2964046515","https://openalex.org/W2995917467","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2365264209","https://openalex.org/W962203960","https://openalex.org/W2026999166","https://openalex.org/W4390516098","https://openalex.org/W1996802783","https://openalex.org/W2509431957","https://openalex.org/W4211007821","https://openalex.org/W2802395037","https://openalex.org/W4389565704","https://openalex.org/W1976216854"],"abstract_inverted_index":{"The":[0,35],"share":[1],"prices":[2],"of":[3,77],"listed":[4],"companies":[5],"in":[6,49,94],"the":[7,90,95,101,150,198,204],"stock":[8],"trading":[9],"market":[10],"are":[11,117],"prone":[12],"to":[13,25,70,164],"be":[14,44,56],"influenced":[15],"by":[16,191],"various":[17],"events.":[18,34],"Performing":[19],"event":[20,67,79,96,107,145],"detection":[21],"could":[22,43,55],"help":[23],"people":[24],"timely":[26],"identify":[27],"investment":[28],"risks":[29],"and":[30,52,99,160,185,201],"opportunities":[31],"accompanying":[32],"these":[33],"financial":[36,140,180],"events":[37,54],"inherently":[38],"present":[39],"hierarchical":[40,60,78,83,91,102,131,165],"structures,":[41],"which":[42],"represented":[45],"as":[46,58,108],"tree-structured":[47],"schemes":[48],"real-life":[50],"applications,":[51],"detecting":[53],"modeled":[57],"a":[59,71,75,129,139,168,178],"multi-label":[61,84,132],"text":[62,85,133],"classification":[63,86,97,134],"problem,":[64],"where":[65,111],"an":[66,106],"is":[68],"designated":[69],"tree":[72],"node":[73],"with":[74,105,119,143,167,182],"sequence":[76],"category":[80,146],"labels.":[81,147],"Conventional":[82],"methods":[87],"usually":[88],"ignore":[89],"relationships":[92],"existing":[93],"scheme,":[98],"treat":[100],"labels":[103,166],"associated":[104],"uniform":[109],"labels,":[110,184],"correct":[112],"or":[113,122],"wrong":[114],"label":[115],"predictions":[116],"assigned":[118],"equal":[120],"rewards":[121],"penalties.":[123],"In":[124],"this":[125],"paper,":[126],"we":[127],"propose":[128],"neural":[130],"method,":[135],"namely":[136],"F-HMTC,":[137],"for":[138],"application":[141],"scenario":[142],"massive":[144],"F-HMTC":[148,186],"learns":[149],"latent":[151],"features":[152],"based":[153],"on":[154,177,203],"bidirectional":[155],"encoder":[156],"representations":[157],"from":[158],"transformers,":[159],"directly":[161],"maps":[162],"them":[163],"delicate":[169],"hierarchy-based":[170],"loss":[171],"layer.":[172],"We":[173,194],"conduct":[174],"extensive":[175],"experiments":[176],"private":[179],"dataset":[181,202],"elaborately-annotated":[183],"consistently":[187],"outperforms":[188],"state-of-art":[189],"baselines":[190],"substantial":[192],"margins.":[193],"will":[195],"release":[196],"both":[197],"source":[199],"codes":[200],"first":[205],"author's":[206],"repository.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}