{"id":"https://openalex.org/W4393094484","doi":"https://doi.org/10.3233/jifs-237323","title":"WLEDD: Legal judgment prediction with legal feature word subgraph label-embedding and dual-knowledge distillation","display_name":"WLEDD: Legal judgment prediction with legal feature word subgraph label-embedding and dual-knowledge distillation","publication_year":2024,"publication_date":"2024-03-22","ids":{"openalex":"https://openalex.org/W4393094484","doi":"https://doi.org/10.3233/jifs-237323"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-237323","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-237323","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems: Applications in Engineering and Technology","raw_type":"journal-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/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"],"raw_orcid":null,"affiliations":[{"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/A5102006887","display_name":"Yidian Lin","orcid":"https://orcid.org/0000-0001-8453-7478"},"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":true,"raw_author_name":"Yidian Lin","raw_affiliation_strings":["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"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5102006887"],"corresponding_institution_ids":["https://openalex.org/I141962983"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05501207,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"49","issue":"1","first_page":"260","last_page":"272"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13643","display_name":"Artificial Intelligence in Law","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9894999861717224,"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":0.9750000238418579,"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/dual","display_name":"Dual (grammatical number)","score":0.7031933069229126},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.621100664138794},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5522003769874573},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5372357964515686},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.516005277633667},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4972892105579376},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.49556219577789307},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.43685758113861084},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35258007049560547},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2683841586112976},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.14809194207191467},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.08234047889709473}],"concepts":[{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.7031933069229126},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.621100664138794},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5522003769874573},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5372357964515686},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.516005277633667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4972892105579376},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.49556219577789307},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43685758113861084},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35258007049560547},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2683841586112976},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.14809194207191467},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.08234047889709473},{"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:10.3233/jifs-237323","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-237323","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems: Applications in Engineering and Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1494159381","https://openalex.org/W1979482500","https://openalex.org/W2164386086","https://openalex.org/W2962893388","https://openalex.org/W2963864497","https://openalex.org/W2963912736","https://openalex.org/W2965006690","https://openalex.org/W2997666887","https://openalex.org/W2998363478","https://openalex.org/W3005193778","https://openalex.org/W3015394728","https://openalex.org/W3022281166","https://openalex.org/W3034892514","https://openalex.org/W3034906024","https://openalex.org/W3035392611","https://openalex.org/W3104871628","https://openalex.org/W3116365291","https://openalex.org/W3156638011","https://openalex.org/W3156831596","https://openalex.org/W3173549151","https://openalex.org/W3176120057","https://openalex.org/W3209145439","https://openalex.org/W3213432680","https://openalex.org/W4285202066","https://openalex.org/W4296878633","https://openalex.org/W4308787184"],"related_works":["https://openalex.org/W4288407670","https://openalex.org/W947140380","https://openalex.org/W2015499252","https://openalex.org/W2911655849","https://openalex.org/W4286432911","https://openalex.org/W4230884544","https://openalex.org/W4245453790","https://openalex.org/W3194985222","https://openalex.org/W3216571906","https://openalex.org/W4214830338"],"abstract_inverted_index":{"Legal":[0],"judgment":[1,39],"prediction(LJP)":[2],"has":[3,57,196,210],"achieved":[4],"remarkable":[5],"results.":[6,31,160],"However,":[7],"existing":[8],"methods":[9],"still":[10],"face":[11],"problems":[12],"such":[13],"as":[14,97],"difficulties":[15],"in":[16,116,119],"obtaining":[17],"key":[18],"feature":[19,44,90],"words":[20],"for":[21,193],"charges,":[22],"which":[23],"impose":[24],"limitations":[25],"on":[26,171],"the":[27,63,78,83,111,145,149,153,164,180,185,188,207],"improvement":[28],"of":[29,65,105,113,125,155,166,191,201,215],"prediction":[30,40,159,195],"To":[32,61,109],"this":[33],"end,":[34],"we":[35,76,94,121,143,220],"propose":[36],"a":[37,129],"legal":[38,43,89,106],"model":[41,131],"with":[42,52,132,184],"Word":[45],"subgraph":[46],"Label-Embedding":[47],"and":[48,71,88,135,227],"Dual-knowledge":[49],"Distillation(WLEDD).":[50],"Compared":[51,183],"traditional":[53],"methods,":[54],"our":[55,176],"method":[56],"two":[58],"contributions:":[59],"(1)":[60],"mitigate":[62],"impact":[64],"overly":[66],"sparse":[67],"tail":[68],"class":[69],"data":[70],"high":[72,114],"similarity":[73],"text":[74],"representations,":[75],"capture":[77],"critical":[79],"features":[80],"related":[81],"to":[82,100,127,151],"charges":[84],"by":[85,157,198,212],"fusing":[86],"LDA":[87],"word":[91],"subgraphs.":[92],"Then":[93],"encode":[95],"them":[96],"label":[98],"information":[99],"obtain":[101],"highly":[102],"distinguished":[103],"representations":[104],"documents.":[107],"(2)":[108],"solve":[110],"problem":[112],"difficulty":[115,165],"some":[117],"subtasks":[118,150],"LJP,":[120],"perform":[122],"subtask-oriented":[123],"compression":[124],"models":[126],"construct":[128],"student":[130],"lower":[133],"complexity":[134],"higher":[136],"accuracy":[137],"through":[138,224],"dual":[139],"knowledge":[140],"distillation.":[141],"Moreover,":[142],"exploit":[144],"logical":[146],"association":[147],"between":[148],"constrain":[152],"labels":[154],"articles":[156],"charge":[158,194],"It":[161],"greatly":[162],"reduces":[163],"article":[167,205],"prediction.":[168],"Experimental":[169],"results":[170],"four":[172],"datasets":[173],"show":[174],"that":[175],"approach":[177],"significantly":[178],"outperforms":[179],"baseline":[181],"models.":[182],"state-of-art":[186],"method,":[187],"F1":[189,208],"value":[190,209],"WLEDD":[192],"increased":[197,211],"an":[199,213],"average":[200,214],"2.57%":[202],".":[203,217],"For":[204],"prediction,":[206],"1.09%":[216],"In":[218],"addition,":[219],"demonstrate":[221],"its":[222],"effectiveness":[223],"ablation":[225],"experiments":[226],"analytical":[228],"experiments.":[229]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
