We describe a methodology for the automatic classificationof legal cases expressed in natural language, which relieson existing legal ontologies and a commonsense knowledgebase. This methodology is founded on a process consisting ofthree phases: an enrichment of a given legal ontology by as-sociating its terms with topics retrieved from the Wikipediaknowledge base; an extraction of relevant concepts from agiven textual legal case; and a matching between the en-riched ontological terms and the extracted concepts. Such aprocess has been successfully implemented in a correspond-ing tool that is part of a larger framework for self-litigationand legal support for the Italian law
ABSTRACT Legal ontologies are conceptual models of specific parts of the legal domain. They provide ...
Legal ontologies aim to provide a structured representation of legal concepts and their interconnect...
The paper describes a research aimed at defining theoretical and technological components enabling a...
We describe a methodology for the automatic classificationof legal cases expressed in natural ...
We describe a methodology for the automatic classification of legal cases expressed in natural langu...
This paper presents a methodology for helping citizens obtain guidance and training when submitting ...
This paper presents a methodology for helping citizens obtain guidance and training when submitting ...
This paper will be published in P. Casanovas, G. Sartor, M. Biasiotti, M. Fernández-Barrera (Eds.) A...
The paper reports on methodology and preliminary results of a case study in automatically extracting...
Legal ontologies have proved crucial for representing, processing and retrieving legal information, ...
A legal knowledge based system called JUSTICE is presented which can identify heterogeneous represen...
In this paper, we present CRIKE, a data-science approach to automatically detect concrete applicatio...
The paper provides an OWL ontology for legal cases with an instantiation of the legal case Popov v. ...
Legal ontologies have proved crucial for representing, processing and retrieving legal information, ...
International audienceThe main goal of our research is to build a legal reasoning system that perfor...
ABSTRACT Legal ontologies are conceptual models of specific parts of the legal domain. They provide ...
Legal ontologies aim to provide a structured representation of legal concepts and their interconnect...
The paper describes a research aimed at defining theoretical and technological components enabling a...
We describe a methodology for the automatic classificationof legal cases expressed in natural ...
We describe a methodology for the automatic classification of legal cases expressed in natural langu...
This paper presents a methodology for helping citizens obtain guidance and training when submitting ...
This paper presents a methodology for helping citizens obtain guidance and training when submitting ...
This paper will be published in P. Casanovas, G. Sartor, M. Biasiotti, M. Fernández-Barrera (Eds.) A...
The paper reports on methodology and preliminary results of a case study in automatically extracting...
Legal ontologies have proved crucial for representing, processing and retrieving legal information, ...
A legal knowledge based system called JUSTICE is presented which can identify heterogeneous represen...
In this paper, we present CRIKE, a data-science approach to automatically detect concrete applicatio...
The paper provides an OWL ontology for legal cases with an instantiation of the legal case Popov v. ...
Legal ontologies have proved crucial for representing, processing and retrieving legal information, ...
International audienceThe main goal of our research is to build a legal reasoning system that perfor...
ABSTRACT Legal ontologies are conceptual models of specific parts of the legal domain. They provide ...
Legal ontologies aim to provide a structured representation of legal concepts and their interconnect...
The paper describes a research aimed at defining theoretical and technological components enabling a...