Caroline Privault

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Identifying potentially responsive data using keyword searches (and their variants) has become standard operating procedure in large-scale document reviews in litigation, regulatory inquiries and subpoena compliance. At the same time, there is growing skepticism within the legal community as to the adequacy of such an approach. Developments in information(More)
This paper describes a tool for assisting lawyers and paralegal teams during document review in eDiscovery. The tool combines a machine learning technology (CategoriX) and advanced multi-touch interface capable of not only addressing the usual cost, time and accuracy issues in document review, but also of facilitating the work of the review teams by(More)
In this paper we examine the use of machine learning classifiers utilized in technologyassisted review (TAR) and, more specifically, the multi-pass manual coding process that supports the training and testing of these classifiers. Manual document coding is known to be subject to error, misinterpretation, and disagreement in reviews conducted for litigation(More)
As advanced technologies, such as data mining become part of the everyday workflow of document reviews in litigations, keyword-search still appears to serve as a cornerstone approach in responsive or privilege review. Keywords are conceptually easy to understand and help culling documents at the early stages of the review. But developing proper keywords to(More)
The classical k-server problem has been widely used to model two-level memory systems (e.g., paging and caching). The problem is to plan the movements of k mobile servers on the vertices of a graph under an on-line sequence of requests. We generalize this model in order to process a sequence of bulk requests and formulate, in this way, a valid model for the(More)
This paper presents Disco, a prototype for supporting knowledge workers in exploring, reviewing and sorting collections of textual data. The goal is to facilitate, accelerate and improve the discovery of information. To this end, it combines Semantic Relatedness techniques with a review workflow developed in a tangible environment. Disco uses a semantic(More)
This paper describes a tool for assisting lawyers and paralegal teams during document review in eDiscovery. The tool combines a machine learning technology (CategoriX) and advanced multitouch interface capabilities to not only address the usual cost, time and accuracy issues in document review, but to also facilitate the work of the review teams by(More)
The problem addressed in this paper is a tool switching problem on a single numerically controlled machine. In the first part, the sequence of jobs is given and the tooling aspect is dealt with: the uniform case where all switching times are equal is described, and a model for the general nonuniform case is proposed. This problem is reduced to the problem(More)
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