Stratify Legal Discovery
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منابع مشابه
E-Discovery: Towads a Narrative Representation Approach to Enhance Predictive Coding-based Review
In the evidential reasoning of human beings, stories play a role in providing an analytic account of the facts. In a legal aspect, the approach of legal reasoning, based on the notion of narratives with evidence, needs to be investigated and supported. The study aims to understand how lawyers cognitively process e-discovery cases, in order to find out the use of narrative in the e-discovery of ...
متن کاملStrategies for Truth Discovery under Resource Constraints ( Extended Abstract )
We present a decision-theoretic approach for sampling information sources in resource-constrained environments, where there is uncertainty regarding source trustworthiness. We exploit diversity among sources to stratify the population into homogeneous subgroups to both minimise redundant sampling and mitigate the effect of source collusion. We show through empirical evaluation that our model is...
متن کاملStrategies for Truth Discovery under Resource Constraints
We present a decision-theory based approach for efficiently sampling information sources in resource-constrained environments, where there is uncertainty regarding source trustworthiness. We exploit diversity among sources to stratify the population into homogeneous subgroups to both minimise redundant sampling and mitigate the effect of certain biases (e.g., source collusion). After presenting...
متن کاملEvaluation of Query Formulations in the Negotiated Query Refinement Process of Legal e-Discovery: UMKC at TREC 2007 Legal Track
UMKC participated in the 2007 legal track. Our experiments focused mainly on evaluating the different query formulations in the negotiated query refinement process of legal e-discovery. For our study, we considered three sets of paired runs in vector space model and language model respectively. Our experiments indicated that although the Boolean query negotiating process was successful for the ...
متن کامل"Time for Some Traffic Problems": Enhancing E-Discovery and Big Data Processing Tools with Linguistic Methods for Deception Detection
Linguistic deception theory provides methods to discover potentially deceptive texts to make them accessible to clerical review. This paper proposes the integration of these linguistic methods with traditional e-discovery techniques to identify deceptive texts within a given author’s larger body of written work, such as their sent email box. First, a set of linguistic features associated with d...
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