Retrieval of Case Law to Provide Layman with Information about Liability: Preliminary Results of the BEST-Project

Uijttenbroek, Elisabeth M.; Lodder, A.R.; Klein, Michel; Wildeboer, Gwen R.; Steenbergen, Wouter van; Sie, Rory; Huygen, Paul; Harmelen, Frank van

doi:10.1007/978-3-540-85569-9_19

Cited by 9 publications

(6 citation statements)

References 9 publications

(7 reference statements)

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“…Their average precision and recall were 89 % and 78 % respectively. Similar analysis holds for [12], [25], which used a thesaurus-based approach. We affirm, therefore, that an ontology-based approach is most appropriate for implementing a semantic retrieval system for case law.…”

Section: System Evaluation and Resultsmentioning

confidence: 68%

“…The studies [12] and [25] (both works appear technically equivalent) developed a system for the retrieval of tort/liability case law for the Netherlands using thesaurus. Thesaurus is a weak conceptualisation of domain concept and this obviously accounts for the poor correctness or reliability of the retrieval system.…”

Section: Related Workmentioning

confidence: 99%

“…The ratio decidendi encompasses both the principles of law on which a judicial verdict was based and the verdict itself; while the obiter dicta hold the facts that were not considered in a case to arrive at a judicial decision. Some of the existing works that involve semantic representations of case law [1], [11], [12], [16], [25] only considered case law in either of its partsratio decidendi or obiter dicta. This paper semantically represents case law without excluding any of its parts.…”

Section: Introductionmentioning

confidence: 99%

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A Semantic Retrieval System for Case Law

Ebietomere

Ekuobase

2019

Applied Computer Systems

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Legal reasoning, the core of legal practice in many countries, is “stare decisis” and its soundness is usually strengthened by relevant case law consulted. However, the task of relevant case law access and retrieval is tiring to legal practitioners and constitutes a serious drain on their productivity. Existing efforts at addressing this problem are conceptional, restrictive or unreliable. Specifically, existing semantic retrieval (SR) systems for case law are desirous of exceptional retrieval precision. Ontology promises to meet this desire, if introduced to the SR system. As a consequence, an ontology-based SR system for case law has been built using the systems analysis and design methodology. In particular, the component-based software engineering and the agile methodologies are employed to implement the system. Finally, the search and retrieval performance of the resultant SR system has been evaluated using the heuristics evaluation method. The retrieval system has shown to have a search and retrieval performance of about 94 % precision, 80 % recall and 84 % F-measure. Overall, the paper implements the SR system for case law with excellent precision and affirms the superiority of ontology approach over other semantic approaches to SR systems for document retrieval in the legal domain.

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Section: System Evaluation and Resultsmentioning

confidence: 68%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Semantic Retrieval System for Case Law

Ebietomere

Ekuobase

2019

Applied Computer Systems

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“…Boolean and natural language 5.1 [32,41,115] Conceptual search and case-based retrieval 5.2 [77,118] Question answering 5.3 [35,88] Query expansion 5.4 [15,30,100] Query reduction 5.5 [70][71][72] Search Result Diversification 5.6 [61] Use of citation networks 5.7 [92,126] Deeper understanding of texts 5.8 [19,43,85,106] Table 3. Summary of methods and main works examined in this survey that comprise these methods.…”

Section: Methods Section Main Work Examinedmentioning

confidence: 99%

Case law retrieval: problems, methods, challenges and evaluations in the last 20 years

Locke¹,

Zuccon²

2022

Preprint

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Case law retrieval is the retrieval of judicial decisions relevant to a legal question. Case law retrieval comprises a significant amount of a lawyer's time, and is important to ensure accurate advice and reduce workload. We survey methods for case law retrieval from the past 20 years and outline the problems and challenges facing evaluation of case law retrieval systems going forward. Limited published work has focused on improving ranking in ad-hoc case law retrieval. But there has been significant work in other areas of case law retrieval, and legal information retrieval generally. This is likely due to legal search providers being unwilling to give up the secrets of their success to competitors. Most evaluations of case law retrieval have been undertaken on small collections and focus on related tasks such as question-answer systems or recommender systems. Work has not focused on Cranfield style evaluations and baselines of methods for case law retrieval on publicly available test collections are not present. This presents a major challenge going forward. But there are reasons to question the extent of this problem, at least in a commercial setting. Without test collections to baseline approaches it cannot be known whether methods are promising. Works by commercial legal search providers show the effectiveness of natural language systems as well as query expansion for case law retrieval. Machine learning is being applied to more and more legal search tasks, and undoubtedly this represents the future of case law retrieval.

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“…The system formulates an influence diagrams to subsequently use game theory to determine a suitable trade-off between claims. Moreover, the BEST-project (Uijttenbroek et al, 2008) provides ontology-based search of law cases to allow parties the opportunity to evaluate claims and liabilities. (For a review on commercial and research initiatives for ODR refer to (Carneiro et al, 2014)).…”

Section: Introductionmentioning

confidence: 99%

eMediation - Towards Smart Online Dispute Resolution

Fersini

Messina

Manenti

et al. 2014

Proceedings of the International Conference on Knowledge Management and Information Sharing

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In this paper, the main requirements towards the next generation of Smart Online Dispute Resolution Systems for eMediation are presented and addressed through the definition of an advanced computational intelligence framework. The main contributions can be distinguished with respect to the parties involved in the eMediation process. Concerning the disputants, the main advancements are related to a smart data collection environment to state the essence of the litigation and an intelligent retrieval of court decisions to improve the awareness of the parties about their liability. Regarding the role of the mediator, the essential point addressed relates to an estimation of disputant flexibility to facilitate the optimal mediation strategies.

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Retrieval of Case Law to Provide Layman with Information about Liability: Preliminary Results of the BEST-Project

Cited by 9 publications

References 9 publications

A Semantic Retrieval System for Case Law

A Semantic Retrieval System for Case Law

Case law retrieval: problems, methods, challenges and evaluations in the last 20 years

eMediation - Towards Smart Online Dispute Resolution

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