{"id":"https://openalex.org/W4385482989","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191443","title":"ReGRL: An Informative Graph Representation via Hierarchical Recursive Learning for Legal Case Recommendation","display_name":"ReGRL: An Informative Graph Representation via Hierarchical Recursive Learning for Legal Case Recommendation","publication_year":2023,"publication_date":"2023-06-18","ids":{"openalex":"https://openalex.org/W4385482989","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191443"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn54540.2023.10191443","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn54540.2023.10191443","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5108049724","display_name":"Xueyuan Chen","orcid":"https://orcid.org/0000-0003-0493-839X"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueyuan Chen","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University,Shanghai,China","School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I141962983"]},{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101703681","display_name":"Xiao Wei","orcid":"https://orcid.org/0000-0002-6258-6129"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Wei","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University,Shanghai,China","School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I141962983"]},{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062917240","display_name":"Hang Yu","orcid":"https://orcid.org/0000-0003-3444-9992"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Yu","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University,Shanghai,China","School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I141962983"]},{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100426947","display_name":"Xiangfeng Luo","orcid":"https://orcid.org/0000-0003-4577-9241"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luo Xiangfeng","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University,Shanghai,China","School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I141962983"]},{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I141962983"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13643","display_name":"Artificial Intelligence in Law","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/3320","display_name":"Political Science and International Relations"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13643","display_name":"Artificial Intelligence in Law","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/3320","display_name":"Political Science and International Relations"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9825999736785889,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.9434999823570251,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"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":0.7382150292396545},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6344829201698303},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5830297470092773},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.5672444701194763},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.508274495601654},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.46004605293273926},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4160492420196533},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41568320989608765},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.30204880237579346}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7382150292396545},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6344829201698303},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5830297470092773},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.5672444701194763},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.508274495601654},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.46004605293273926},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4160492420196533},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41568320989608765},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30204880237579346},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn54540.2023.10191443","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn54540.2023.10191443","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W40010561","https://openalex.org/W74055483","https://openalex.org/W1492230849","https://openalex.org/W1978394996","https://openalex.org/W2025167103","https://openalex.org/W2056562706","https://openalex.org/W2088368771","https://openalex.org/W2097308346","https://openalex.org/W2099438806","https://openalex.org/W2117420919","https://openalex.org/W2131681506","https://openalex.org/W2131744502","https://openalex.org/W2154851992","https://openalex.org/W2156718197","https://openalex.org/W2164281374","https://openalex.org/W2606780347","https://openalex.org/W2737925311","https://openalex.org/W2887092413","https://openalex.org/W2890026792","https://openalex.org/W2896457183","https://openalex.org/W2916106175","https://openalex.org/W2961295589","https://openalex.org/W2962756421","https://openalex.org/W2964015378","https://openalex.org/W2979750740","https://openalex.org/W2995509183","https://openalex.org/W2996910652","https://openalex.org/W3019011053","https://openalex.org/W3034440122","https://openalex.org/W3034892514","https://openalex.org/W3035668167","https://openalex.org/W3094504436","https://openalex.org/W3099768174","https://openalex.org/W3104097132","https://openalex.org/W3117737817","https://openalex.org/W3141286420","https://openalex.org/W3156716744","https://openalex.org/W3204622772","https://openalex.org/W3208204411","https://openalex.org/W4214492518","https://openalex.org/W4285723986","https://openalex.org/W4287891026","https://openalex.org/W4294170691","https://openalex.org/W4294558607","https://openalex.org/W6679775712","https://openalex.org/W6682691769","https://openalex.org/W6682755970","https://openalex.org/W6726873649","https://openalex.org/W6736685754","https://openalex.org/W6738964360","https://openalex.org/W6741450815","https://openalex.org/W6755207826","https://openalex.org/W6760001035","https://openalex.org/W6765543928"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W2999756192","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W936373746","https://openalex.org/W2975817033","https://openalex.org/W4382701072"],"abstract_inverted_index":{"Legal":[0],"Case":[1],"Recommendation":[2],"(LCR)":[3],"is":[4,44],"to":[5,14,46,69,84,99,124,158,171],"find":[6],"out":[7],"the":[8,15,19,25,36,49,72,75,87,127,130,173,179],"documents":[9,27],"that":[10,143],"are":[11,28],"most":[12],"similar":[13],"input":[16],"case":[17,136],"from":[18],"judicial":[20],"point":[21],"of":[22,56,102,129,175,181],"view.":[23],"Since":[24],"legal":[26,34,50],"long":[29],"texts":[30],"and":[31,77,93,113,133,177],"have":[32],"strong":[33],"attributes,":[35],"traditional":[37],"recommendation":[38],"method":[39],"based":[40],"on":[41],"text":[42,159],"similarity":[43],"difficult":[45],"accurately":[47,85],"understand":[48,86],"documents,":[51],"resulting":[52],"in":[53,74,117],"poor":[54],"effect":[55],"LCR.":[57,139,163],"To":[58,105],"address":[59],"this":[60],"problem,":[61],"we":[62,166],"propose":[63],"Recursive":[64],"Graph":[65],"Representation":[66],"Learning":[67],"(ReGRL)":[68],"hierarchically":[70],"learn":[71],"information":[73,95,101],"graph,":[76],"obtain":[78],"a":[79,118,149,154],"more":[80],"informative":[81],"graph":[82,111,115],"representation":[83,160],"case.":[88],"ReGRL":[89,108,123,144,176],"captures":[90],"nodes,":[91],"edge,":[92],"community":[94],"at":[96],"different":[97,103,169],"levels":[98],"integrate":[100],"granularity.":[104],"achieve":[106],"this,":[107],"performs":[109],"top-down":[110],"decomposition":[112],"bottom-up":[114],"encoding":[116],"recursive":[119,182],"form,":[120],"which":[121],"allows":[122],"flexibly":[125],"control":[126],"depth":[128],"learning":[131],"layers":[132],"provide":[134],"accurate":[135],"representations":[137],"for":[138,162],"Experimental":[140],"results":[141],"show":[142],"can":[145],"not":[146],"only":[147],"generate":[148],"good":[150],"representation,":[151],"but":[152],"has":[153],"better":[155],"performance":[156],"compared":[157],"methods":[161],"In":[164],"addition,":[165],"also":[167],"performed":[168],"experiments":[170],"analyze":[172],"principle":[174],"verify":[178],"effectiveness":[180],"procedures.":[183]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
