An overview of memory: some issues on structures and organization in the legal domain

Autores
Kaestner, Celso A. A.; Hasegawa, Fabiano M.; Santos, Emerson L. dos; Avila, Braulio C.
Año de publicación
2003
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Lawyers often need to look for previous similar legal cases when analysing new ones. The more previous cases, the more time is spent. Classical search engines execute termbased retrieval, which may miss relevant documents as well as fetch several irrelevant ones, causing lack of useful information and waste of time. Ideally, retrieval should be meaning-based. Humans beings are able to do e cient searches due to their knowledge. Therefore, semantic search requires knowledge. This paper presents a semantic search engine. Along the paper, several issues concerning specially knowledge representation and memory are discussed. A formalism based on models of comprehension is introduced, as well as its motivation. Examples of representation of sentences in natural language from the Legal Domain are provided. The search engine and its architecture, based on domain knowledge, are brie y commented. The main goal is to give legal o ces the opportunity to save time by providing a more suitable document retrieval.
Eje: Agentes y Sistemas Inteligentes (ASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Semantic Representation of Legal Documents
Semantic Document Retrieval
Semantics
ARTIFICIAL INTELLIGENCE
Intelligent agents
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/22712
Acceder
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network_name_str SEDICI (UNLP)
spelling An overview of memory: some issues on structures and organization in the legal domainKaestner, Celso A. A.Hasegawa, Fabiano M.Santos, Emerson L. dosAvila, Braulio C.Ciencias InformáticasSemantic Representation of Legal DocumentsSemantic Document RetrievalSemanticsARTIFICIAL INTELLIGENCEIntelligent agentsLawyers often need to look for previous similar legal cases when analysing new ones. The more previous cases, the more time is spent. Classical search engines execute termbased retrieval, which may miss relevant documents as well as fetch several irrelevant ones, causing lack of useful information and waste of time. Ideally, retrieval should be meaning-based. Humans beings are able to do e cient searches due to their knowledge. Therefore, semantic search requires knowledge. This paper presents a semantic search engine. Along the paper, several issues concerning specially knowledge representation and memory are discussed. A formalism based on models of comprehension is introduced, as well as its motivation. Examples of representation of sentences in natural language from the Legal Domain are provided. The search engine and its architecture, based on domain knowledge, are brie y commented. The main goal is to give legal o ces the opportunity to save time by providing a more suitable document retrieval.Eje: Agentes y Sistemas Inteligentes (ASI)Red de Universidades con Carreras en Informática (RedUNCI)2003-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf542-553http://sedici.unlp.edu.ar/handle/10915/22712enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:55:08Zoai:sedici.unlp.edu.ar:10915/22712Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:08.323SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv An overview of memory: some issues on structures and organization in the legal domain
title An overview of memory: some issues on structures and organization in the legal domain
spellingShingle An overview of memory: some issues on structures and organization in the legal domain
Kaestner, Celso A. A.
Ciencias Informáticas
Semantic Representation of Legal Documents
Semantic Document Retrieval
Semantics
ARTIFICIAL INTELLIGENCE
Intelligent agents
title_short An overview of memory: some issues on structures and organization in the legal domain
title_full An overview of memory: some issues on structures and organization in the legal domain
title_fullStr An overview of memory: some issues on structures and organization in the legal domain
title_full_unstemmed An overview of memory: some issues on structures and organization in the legal domain
title_sort An overview of memory: some issues on structures and organization in the legal domain
dc.creator.none.fl_str_mv Kaestner, Celso A. A.
Hasegawa, Fabiano M.
Santos, Emerson L. dos
Avila, Braulio C.
author Kaestner, Celso A. A.
author_facet Kaestner, Celso A. A.
Hasegawa, Fabiano M.
Santos, Emerson L. dos
Avila, Braulio C.
author_role author
author2 Hasegawa, Fabiano M.
Santos, Emerson L. dos
Avila, Braulio C.
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Semantic Representation of Legal Documents
Semantic Document Retrieval
Semantics
ARTIFICIAL INTELLIGENCE
Intelligent agents
topic Ciencias Informáticas
Semantic Representation of Legal Documents
Semantic Document Retrieval
Semantics
ARTIFICIAL INTELLIGENCE
Intelligent agents
dc.description.none.fl_txt_mv Lawyers often need to look for previous similar legal cases when analysing new ones. The more previous cases, the more time is spent. Classical search engines execute termbased retrieval, which may miss relevant documents as well as fetch several irrelevant ones, causing lack of useful information and waste of time. Ideally, retrieval should be meaning-based. Humans beings are able to do e cient searches due to their knowledge. Therefore, semantic search requires knowledge. This paper presents a semantic search engine. Along the paper, several issues concerning specially knowledge representation and memory are discussed. A formalism based on models of comprehension is introduced, as well as its motivation. Examples of representation of sentences in natural language from the Legal Domain are provided. The search engine and its architecture, based on domain knowledge, are brie y commented. The main goal is to give legal o ces the opportunity to save time by providing a more suitable document retrieval.
Eje: Agentes y Sistemas Inteligentes (ASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description Lawyers often need to look for previous similar legal cases when analysing new ones. The more previous cases, the more time is spent. Classical search engines execute termbased retrieval, which may miss relevant documents as well as fetch several irrelevant ones, causing lack of useful information and waste of time. Ideally, retrieval should be meaning-based. Humans beings are able to do e cient searches due to their knowledge. Therefore, semantic search requires knowledge. This paper presents a semantic search engine. Along the paper, several issues concerning specially knowledge representation and memory are discussed. A formalism based on models of comprehension is introduced, as well as its motivation. Examples of representation of sentences in natural language from the Legal Domain are provided. The search engine and its architecture, based on domain knowledge, are brie y commented. The main goal is to give legal o ces the opportunity to save time by providing a more suitable document retrieval.
publishDate 2003
dc.date.none.fl_str_mv 2003-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/22712
url http://sedici.unlp.edu.ar/handle/10915/22712
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
542-553
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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