{"id":"https://openalex.org/W4323520210","doi":"https://doi.org/10.1145/3578741.3578787","title":"Causal Pattern Representation Learning for Extracting Causality from Literature","display_name":"Causal Pattern Representation Learning for Extracting Causality from Literature","publication_year":2022,"publication_date":"2022-12-23","ids":{"openalex":"https://openalex.org/W4323520210","doi":"https://doi.org/10.1145/3578741.3578787"},"language":"en","primary_location":{"id":"doi:10.1145/3578741.3578787","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3578741.3578787","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Machine Learning and Natural Language Processing","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/A5079824167","display_name":"Jiaoyun Yang","orcid":"https://orcid.org/0000-0002-0233-590X"},"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":true,"raw_author_name":"Jiaoyun Yang","raw_affiliation_strings":["Hefei University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090022090","display_name":"Hao Xiong","orcid":"https://orcid.org/0000-0002-5037-7530"},"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":"Hao Xiong","raw_affiliation_strings":["Hefei University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081959815","display_name":"Hongjin Zhang","orcid":"https://orcid.org/0000-0003-2754-2769"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongjin Zhang","raw_affiliation_strings":["Bepsun Eurotech Solution Oy, Finland"],"affiliations":[{"raw_affiliation_string":"Bepsun Eurotech Solution Oy, Finland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091586702","display_name":"Min Hu","orcid":"https://orcid.org/0000-0003-2122-0240"},"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":"Min Hu","raw_affiliation_strings":["Hefei University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100651298","display_name":"Ning An","orcid":"https://orcid.org/0000-0003-3317-5299"},"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":"Ning An","raw_affiliation_strings":["Hefei University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, China","institution_ids":["https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5079824167"],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":null,"apc_paid":null,"fwci":0.4137,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.69651422,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"229","last_page":"233"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9991000294685364,"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":0.9957000017166138,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7839372754096985},{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.7247445583343506},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6004695892333984},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5799058079719543},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.548899233341217},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5128629207611084},{"id":"https://openalex.org/keywords/directed-acyclic-graph","display_name":"Directed acyclic graph","score":0.43542835116386414},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.43478891253471375},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.42590320110321045},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4160372018814087},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36617839336395264},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12771204113960266}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7839372754096985},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.7247445583343506},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6004695892333984},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5799058079719543},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.548899233341217},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5128629207611084},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.43542835116386414},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.43478891253471375},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.42590320110321045},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4160372018814087},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36617839336395264},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12771204113960266},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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:10.1145/3578741.3578787","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3578741.3578787","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Machine Learning and Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G6515849855","display_name":null,"funder_award_id":"62072153","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1902237438","https://openalex.org/W2123442489","https://openalex.org/W2517194566","https://openalex.org/W2602331152","https://openalex.org/W2608420543","https://openalex.org/W2885051956","https://openalex.org/W2887428522","https://openalex.org/W2892094955","https://openalex.org/W2970778761","https://openalex.org/W2984452801","https://openalex.org/W3006513641","https://openalex.org/W3086041321","https://openalex.org/W3194836374","https://openalex.org/W4285280118","https://openalex.org/W6675557394"],"related_works":["https://openalex.org/W842810586","https://openalex.org/W4319940250","https://openalex.org/W2352298027","https://openalex.org/W2092919065","https://openalex.org/W3138801416","https://openalex.org/W4236762297","https://openalex.org/W2444550338","https://openalex.org/W2369351710","https://openalex.org/W2594363579","https://openalex.org/W2169232658"],"abstract_inverted_index":{"Extracting":[0],"causality":[1,57,135,156,167],"from":[2],"literature":[3,52,129],"has":[4],"become":[5],"an":[6],"important":[7],"task":[8,165],"due":[9,39],"to":[10,21,40,64,85,105,120],"the":[11,54,67,90,95,99,110,149,164],"essential":[12],"role":[13],"of":[14,56,69,143,151,166],"causality.":[15],"Traditional":[16],"methods":[17],"use":[18],"pattern":[19,72],"matching":[20],"extract":[22],"causality,":[23],"requiring":[24],"domain":[25],"knowledge":[26],"and":[27,76,112,158],"extensive":[28],"human":[29],"effort.":[30],"Recent":[31],"researches":[32],"focus":[33,65],"on":[34,66,98,124,146,163],"utilizing":[35],"pre-trained":[36],"language":[37],"models":[38],"their":[41],"success":[42],"in":[43,51],"Natural":[44],"Language":[45],"Processing":[46],"(NLP).":[47],"However,":[48],"long":[49],"sentences":[50],"hinders":[53],"performance":[55],"extraction.":[58,168],"In":[59],"this":[60,87],"paper,":[61],"we":[62,131],"propose":[63],"representation":[68],"causal":[70],"virtual":[71],"<head_entity,":[73],"causal_virtual_trigger,":[74],"tail_entity>":[75],"design":[77],"a":[78,133,141],"Causal":[79],"Pattern":[80],"Representation":[81],"Learning":[82],"(CPRL)":[83],"method":[84],"tackle":[86],"challenge.":[88],"For":[89,109],"causal_virtual_trigger":[91],"representation,":[92,114],"CPRL":[93,115],"applies":[94,116],"attention":[96],"mechanism":[97],"shortest":[100],"dependency":[101,123],"path":[102],"between":[103],"entities":[104],"filter":[106],"irrelevant":[107],"information.":[108],"head_entity":[111],"tail_entity":[113],"graph":[117],"convolution":[118],"networks":[119],"encode":[121],"word":[122],"entities.":[125],"By":[126],"crawling":[127],"health-related":[128],"abstracts,":[130],"create":[132],"new":[134],"extraction":[136,157,161],"dataset,":[137],"namely":[138],"HealthCE,":[139],"with":[140],"size":[142],"3479.":[144],"Experiments":[145],"HealthCE":[147],"demonstrate":[148],"effectiveness":[150],"our":[152],"approach":[153],"over":[154],"existing":[155],"general":[159],"relation":[160],"baselines":[162]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
