Eunomos, a legal document and knowledge management system for the Web to provide relevant, reliable and up-to-date information on the law

Boella, Guido; Di, Luigi; Humphreys, Llio; Robaldo, Livio; Rossi, Piercarlo; Torre, Leendert van der

doi:10.1007/s10506-016-9184-3

Cited by 71 publications

(45 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This requires in-depth legal knowledge, analysis of search engine log files and continuous maintenance. Semi-automated classification using ontologies (Boella et al 2016) is gaining popularity, and notwithstanding the current hype about legal AI applications like IBM's Ross (Beck 2014), scepticism about their performance seems to be a healthy attitude (Paliwala 2016;Remus and Levy 2016 ). 4.…”

Section: Topical Relevancementioning

confidence: 99%

On the concept of relevance in legal information retrieval

Opijnen¹,

Santos

2017

Artif Intell Law

111

View full text Add to dashboard Cite

The concept of 'relevance' is crucial to legal information retrieval, but because of its intuitive understanding it goes undefined too easily and unexplored too often. We discuss a conceptual framework on relevance within legal information retrieval, based on a typology of relevance dimensions used within general information retrieval science, but tailored to the specific features of legal information. This framework can be used for the development and improvement of legal information retrieval systems.

show abstract

Section: Topical Relevancementioning

confidence: 99%

On the concept of relevance in legal information retrieval

Opijnen¹,

Santos

2017

Artif Intell Law

111

View full text Add to dashboard Cite

show abstract

“…A promising idea to achieve higher recall without crucially lowering the precision could be achieved by integrating the existing statistical system with the rule-based system proposed in [15]. We aim in our long-term research at devising such an hybrid approach and integrating it in our systems for legal informatics [3] [4].…”

Section: Discussionmentioning

confidence: 99%

A unifying similarity measure for automated identification of national implementations of european union directives

Nanda

Boella

et al. 2017

Proceedings of the 16th Edition of the International Conference on Articial Intelligence and Law

Self Cite

View full text Add to dashboard Cite

is paper presents a unifying text similarity measure (USM) for automated identi cation of national implementations of European Union (EU) directives. e proposed model retrieves the transposed provisions of national law at a ne-grained level for each article of the directive. USM incorporates methods for matching common words, common sequences of words and approximate string matching. It was used for identifying transpositions on a multilingual corpus of four directives and their corresponding national implementing measures (NIMs) in three di erent languages : English, French and Italian. We further utilized a corpus of four additional directives and their corresponding NIMs in English language for a thorough test of the USM approach. We evaluated the model by comparing our results with a gold standard consisting of o cial correlation tables (where available) or correspondences manually identi ed by domain experts. Our results indicate that USM was able to identify transpositions with average F-score values of 0.808, 0.736 and 0.708 for French, Italian and English Directive-NIM pairs respectively in the multilingual corpus. A comparison with stateof-the-art methods for text similarity illustrates that USM achieves a higher F-score and recall across both the corpora.

show abstract

“…Modern NLP technologies [6] are able to classify and discover inter-links between legal documents thanks to parsers [1], statistical algorithms [8], and legal terminological databases or legal ontologies [40,8]. This is often done by transforming the legal documents into XML standards, such as Akoma Ntoso 8 , where relevant information are tagged.…”

Section: Related Workmentioning

confidence: 99%

Towards Legal Compliance by Correlating Standards and Laws with a Semi-automated Methodology

Bartolini

Giurgiu

Lenzini

et al. 2017

Communications in Computer and Information Science

Self Cite

View full text Add to dashboard Cite

Abstract. Since generally legal regulations do not provide clear parameters to determine when their requirements are met, achieving legal compliance is not trivial. The adoption of standards could help create an argument of compliance in favour of the implementing party, provided there is a clear correspondence between the provisions of a specific standard and the regulation's requirements. However, identifying such correspondences is a complex process which is complicated further by the fact that the established correlations may be overridden in time e.g., because newer court decisions change the interpretation of certain legal provisions. To help solve these problems, we present a framework that supports legal experts in recognizing correlations between provisions in a standard and requirements in a given law. The framework relies on state-of-the-art Natural Language Semantics techniques to process the linguistic terms of the two documents, and maintains a knowledge base of the logic representations of the terms, together with their defeasible correlations, both formal and substantive. An application of the framework is shown by comparing a provision of the European General Data Protection Regulation with the ISO/IEC 27018:2014 standard.

show abstract

Eunomos, a legal document and knowledge management system for the Web to provide relevant, reliable and up-to-date information on the law

Cited by 71 publications

References 34 publications

On the concept of relevance in legal information retrieval

On the concept of relevance in legal information retrieval

A unifying similarity measure for automated identification of national implementations of european union directives

Towards Legal Compliance by Correlating Standards and Laws with a Semi-automated Methodology

Contact Info

Product

Resources

About