{"id":"https://openalex.org/W3118969455","doi":"https://doi.org/10.1109/ssci47803.2020.9308506","title":"Predicting the outcome of judicial cases using semantic analysis","display_name":"Predicting the outcome of judicial cases using semantic analysis","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https://openalex.org/W3118969455","doi":"https://doi.org/10.1109/ssci47803.2020.9308506","mag":"3118969455"},"language":"en","primary_location":{"id":"doi:10.1109/ssci47803.2020.9308506","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci47803.2020.9308506","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","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/A5110735240","display_name":"Rohit Pande","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Rohit Pande","raw_affiliation_strings":["Whitireia Community Polytechnic, Auckland, New Zealand"],"affiliations":[{"raw_affiliation_string":"Whitireia Community Polytechnic, Auckland, New Zealand","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076639190","display_name":"Shafiq Alam","orcid":"https://orcid.org/0000-0002-9566-8040"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Shafiq Alam","raw_affiliation_strings":["University of Auckland, Auckland, New Zealand"],"affiliations":[{"raw_affiliation_string":"University of Auckland, Auckland, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5110735240"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8658,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.84877417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"3","issue":null,"first_page":"1757","last_page":"1761"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13643","display_name":"Artificial Intelligence in Law","score":0.9997000098228455,"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":0.9997000098228455,"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/T12755","display_name":"Legal Education and Practice Innovations","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/3308","display_name":"Law"},"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/T11762","display_name":"Law, Economics, and Judicial Systems","score":0.9704999923706055,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.8354536294937134},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.789569616317749},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.7271033525466919},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6926287412643433},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6755850315093994},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6320565938949585},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.616521954536438},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6130426526069641},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5300011038780212},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5259609222412109},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5146151781082153},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.4914966821670532},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48990148305892944},{"id":"https://openalex.org/keywords/latent-semantic-analysis","display_name":"Latent semantic analysis","score":0.4690205156803131},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.42060309648513794},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40392157435417175},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.2620348036289215}],"concepts":[{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.8354536294937134},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.789569616317749},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7271033525466919},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6926287412643433},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6755850315093994},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6320565938949585},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.616521954536438},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6130426526069641},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5300011038780212},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5259609222412109},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5146151781082153},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.4914966821670532},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48990148305892944},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.4690205156803131},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.42060309648513794},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40392157435417175},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.2620348036289215},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci47803.2020.9308506","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci47803.2020.9308506","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W1880262756","https://openalex.org/W2610681240","https://openalex.org/W2788347302","https://openalex.org/W2858159822","https://openalex.org/W2885141472","https://openalex.org/W2889035831","https://openalex.org/W2890026792","https://openalex.org/W2893709526","https://openalex.org/W2898946357","https://openalex.org/W2922092249","https://openalex.org/W2954257417","https://openalex.org/W2964328740","https://openalex.org/W2979478448","https://openalex.org/W2980808611","https://openalex.org/W2980888783","https://openalex.org/W3007769290","https://openalex.org/W4231510805","https://openalex.org/W6639619044","https://openalex.org/W6752999927","https://openalex.org/W6753255307","https://openalex.org/W6754476681","https://openalex.org/W6755565771","https://openalex.org/W6760278538","https://openalex.org/W6761460703"],"related_works":["https://openalex.org/W4389096007","https://openalex.org/W2726875075","https://openalex.org/W2995939990","https://openalex.org/W1551384396","https://openalex.org/W4283015716","https://openalex.org/W2474958513","https://openalex.org/W31838995","https://openalex.org/W2367339491","https://openalex.org/W3127963682","https://openalex.org/W3092099586"],"abstract_inverted_index":{"The":[0,59,90,102],"provision":[1],"of":[2,30,33,39,96,99,112,118,131,143,152,159],"legal":[3,20],"advice":[4],"based":[5],"on":[6,25,50],"information":[7],"contained":[8],"within":[9,19],"past":[10],"cases":[11,114],"is":[12,148],"considered":[13],"to":[14],"be":[15],"a":[16],"key":[17],"task":[18],"practice.":[21],"This":[22],"study":[23,91,151],"focuses":[24],"the":[26,31,40,51,97,110,132,141,144,149,157],"analysis":[27,67],"and":[28,45,84,120,135],"prediction":[29],"outcomes":[32,111],"employment":[34],"cases.":[35,162],"It":[36,122],"uses":[37],"some":[38],"latest":[41],"deep":[42,106],"learning":[43,107],"methods":[44],"compares":[46],"their":[47,66],"predictive":[48],"performance":[49,98],"New":[52],"Zealand":[53],"Employment":[54],"Relations":[55],"Authority":[56],"(NZERA)":[57],"dataset.":[58],"experiments":[60],"include":[61],"document":[62],"pre-processing":[63],"followed":[64],"by":[65],"with":[68,75,115],"Latent":[69],"Dirichlet":[70],"Allocation":[71],"(LDA)":[72],"in":[73],"conjunction":[74],"Recurrent":[76],"Neural":[77,81,86],"Network":[78,82,87],"(RNN),":[79],"Convolutional":[80],"(CNN)":[83],"Capsule":[85],"(CapsNet)":[88],"models.":[89,101],"also":[92,124],"includes":[93],"an":[94],"evaluation":[95],"these":[100],"findings":[103],"indicate":[104],"that":[105,126],"models":[108,129],"predict":[109],"NZERA":[113],"varying":[116],"levels":[117],"accuracy":[119,134],"consistency.":[121],"was":[123],"found":[125],"CapsNet-based":[127],"LDA":[128],"were":[130],"highest":[133],"consistency":[136],"amongst":[137],"those":[138],"trained.":[139],"To":[140],"best":[142],"authors'":[145],"knowledge":[146],"this":[147],"first":[150],"its":[153],"kind":[154],"which":[155],"analyzes":[156],"semantics":[158],"employment-related":[160],"judicial":[161]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
