{"id":"https://openalex.org/W4392949630","doi":"https://doi.org/10.3233/idt-230566","title":"Judgment prediction from legal documents using Texas wolf optimization based deep BiLSTM model","display_name":"Judgment prediction from legal documents using Texas wolf optimization based deep BiLSTM model","publication_year":2024,"publication_date":"2024-03-19","ids":{"openalex":"https://openalex.org/W4392949630","doi":"https://doi.org/10.3233/idt-230566"},"language":"en","primary_location":{"id":"doi:10.3233/idt-230566","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-230566","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"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":"Intelligent Decision Technologies","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/A5024685706","display_name":"Avadhut Shelar","orcid":null},"institutions":[{"id":"https://openalex.org/I65674248","display_name":"Visvesvaraya Technological University","ror":"https://ror.org/00ha14p11","country_code":"IN","type":"education","lineage":["https://openalex.org/I65674248"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Avadhut Shelar","raw_affiliation_strings":["Department of Computer Science and Engineering, Rashtreeya Vidyalaya College of Engineering, India and Visvesvaraya Technological University, Belagavi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Rashtreeya Vidyalaya College of Engineering, India and Visvesvaraya Technological University, Belagavi, India","institution_ids":["https://openalex.org/I65674248"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010543110","display_name":"Minal Moharir","orcid":"https://orcid.org/0000-0001-8256-5440"},"institutions":[{"id":"https://openalex.org/I65674248","display_name":"Visvesvaraya Technological University","ror":"https://ror.org/00ha14p11","country_code":"IN","type":"education","lineage":["https://openalex.org/I65674248"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Minal Moharir","raw_affiliation_strings":["Department of Computer Science and Engineering, Rashtreeya Vidyalaya College of Engineering, India and Visvesvaraya Technological University, Belagavi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Rashtreeya Vidyalaya College of Engineering, India and Visvesvaraya Technological University, Belagavi, India","institution_ids":["https://openalex.org/I65674248"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5024685706"],"corresponding_institution_ids":["https://openalex.org/I65674248"],"apc_list":null,"apc_paid":null,"fwci":3.4818,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91813923,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"18","issue":"2","first_page":"1557","last_page":"1576"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13643","display_name":"Artificial Intelligence in Law","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9531999826431274,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9528999924659729,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7607263326644897},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6632487773895264},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.6137546300888062},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5990664958953857},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5845891833305359},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.5755507349967957},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5721301436424255},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5625057816505432},{"id":"https://openalex.org/keywords/f1-score","display_name":"F1 score","score":0.47564932703971863},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.46611955761909485},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4317166209220886},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.41648373007774353},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32913392782211304},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32133978605270386},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10276728868484497}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7607263326644897},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6632487773895264},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.6137546300888062},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5990664958953857},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5845891833305359},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.5755507349967957},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5721301436424255},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5625057816505432},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.47564932703971863},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.46611955761909485},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4317166209220886},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.41648373007774353},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32913392782211304},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32133978605270386},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10276728868484497},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/idt-230566","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-230566","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"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":"Intelligent Decision Technologies","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2725692393","https://openalex.org/W2890026792","https://openalex.org/W2912267070","https://openalex.org/W2919979744","https://openalex.org/W2932110532","https://openalex.org/W2962854673","https://openalex.org/W2964085268","https://openalex.org/W2972757121","https://openalex.org/W2980808611","https://openalex.org/W2994033896","https://openalex.org/W3007075806","https://openalex.org/W3095648894","https://openalex.org/W3121249931","https://openalex.org/W3134994309","https://openalex.org/W3135108781","https://openalex.org/W3156443832","https://openalex.org/W3176443840","https://openalex.org/W3184563164","https://openalex.org/W4212818080","https://openalex.org/W4213450276","https://openalex.org/W4249279051","https://openalex.org/W4283274188","https://openalex.org/W4290724847","https://openalex.org/W4386566716","https://openalex.org/W4387491652","https://openalex.org/W6740079799"],"related_works":["https://openalex.org/W2358294942","https://openalex.org/W4367460280","https://openalex.org/W4387490204","https://openalex.org/W4386414453","https://openalex.org/W4388937883","https://openalex.org/W4389848424","https://openalex.org/W4293205612","https://openalex.org/W4352976590","https://openalex.org/W4385349203","https://openalex.org/W4297839701"],"abstract_inverted_index":{"The":[0,29,116,149,173,204],"complicated":[1],"nature":[2],"of":[3,8,20,67,138,151,170,184,198,229],"legal":[4,86,159],"texts,":[5],"a":[6,70],"lack":[7],"labeled":[9],"data,":[10],"concerns":[11],"about":[12],"fairness,":[13],"and":[14,59,96,104,141,156,194,201,219,226,232,247],"difficulties":[15],"with":[16],"interpretation":[17],"represent":[18],"some":[19],"the":[21,81,136,152,211,235,244],"challenges":[22,37],"that":[23],"judicial":[24,98,171],"judgment":[25,160],"prediction":[26],"models":[27],"encounter.":[28],"approach":[30],"we":[31],"propose":[32],"seeks":[33],"to":[34,54,62,84,110,125,146,154],"conquer":[35],"these":[36,121],"by":[38,164],"using":[39,223],"advanced":[40],"techniques":[41,109],"for":[42,91,249],"deep":[43,47,71],"learning,":[44],"such":[45],"as":[46],"Bidirectional":[48],"Long":[49],"Short-Term":[50],"Memory":[51],"(BiLSTM)":[52],"networks":[53],"recognize":[55],"complex":[56],"linguistic":[57],"patterns":[58],"transfer":[60],"learning":[61],"make":[63],"more":[64],"efficient":[65],"use":[66],"data.":[68,99,127,172],"Employing":[69],"BiLSTM":[72],"classifier":[73],"(TWO-BiLSTM)":[74],"model":[75,117,153,174,236],"based":[76,134],"on":[77,135,167],"Texas":[78,130],"wolf":[79,131],"optimization,":[80],"research":[82],"aims":[83],"predict":[85,158],"judgments.":[87],"To":[88],"prepare":[89],"it":[90,93,166],"evaluation,":[92],"initially":[94],"collects":[95],"preprocesses":[97],"Feature":[100],"extraction":[101],"involves":[102],"statistical":[103],"Principal":[105],"component":[106],"Analysis":[107],"(PCA)":[108],"generate":[111],"an":[112,182],"extensive":[113],"feature":[114],"set.":[115],"undergoes":[118],"training":[119],"utilizing":[120],"features":[122],"in":[123,178,191,210],"addition":[124],"preprocessed":[126],"A":[128],"hybrid":[129],"optimization":[132,137],"tactic,":[133],"gray":[139],"wolves":[140],"Harris":[142],"hawks,":[143],"is":[144],"employed":[145],"boost":[147],"performance.":[148,239],"ability":[150],"accurately":[155],"effectively":[157],"has":[161],"been":[162],"demonstrated":[163,209],"testing":[165],"different":[168],"sets":[169],"achieved":[175,188],"reasonably":[176],"well":[177,190],"TP":[179],"90,":[180],"having":[181,196],"accuracy":[183,218],"97.00%.":[185],"It":[186],"also":[187],"exceedingly":[189],"f-score,":[192,224],"precision,":[193,225],"recall,":[195],"scores":[197],"97.29,":[199],"97.10,":[200],"97.19,":[202],"correspondingly.":[203],"model\u2019s":[205,245],"effectiveness":[206,246],"was":[207],"further":[208],"k-fold":[212],"10":[213],"assessment,":[214],"which":[215],"exhibited":[216],"96.00%":[217],"robustness.":[220],"In":[221],"addition,":[222],"recall":[227],"metrics":[228],"96.25,":[230],"96.89,":[231],"95.96,":[233],"respectively,":[234],"showed":[237],"outstanding":[238,241],"These":[240],"results":[242],"demonstrate":[243],"dependability":[248],"providing":[250],"accurate":[251],"predictions.":[252]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2025-10-10T00:00:00"}
