Author Archives: Millnet

DocBuster Introduction

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Shedding some light on computer assisted review/predictive coding

As volumes of material that need to be reviewed increase, the traditional approach of having a reviewer look at each potentially responsive document has become unfeasible. In the last decade lawyers have often resorted to using keywords to “cull” the volume of material and create a more manageable volume of material that is reviewed. Strikingly, such an approach has generally been done without any attempt being made to measure whether the keywords used were effective in finding the substantial bulk of the responsive material – despite there being well established approaches, using statistics, to do just that task.

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Approaching Scanning & Coding

Compared with the huge cost savings that can be achieved when extracting metadata and running searches across ”native” electronic files (.doc .xls. msg. pdf .nsf and so on), working with significant volumes of paper documents is much less efficient. The problem is that the metadata that would otherwise be used to group, sort and filter documents having regard to the author, date, recipient or subject matter of the document is completely missing – all you start with is paper printed with ink that a human – but not a computer – can read.

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Devising an eDiscovery Strategy

Disputes generally centre on a small number of critical documents and the process of identifying, capturing, processing and reviewing material should balance the issues of cost, proportionality and risk work within the applicable procedural Rules. A defensible process should be adopted to manage the process of disclosure. A famous visual “model” of the steps involved in managing data is useful in illustrating how the volume of material at the outset of the process is whittled down whilst the proportion of relevant material goes up during the course of the process has been published by the EDRM.

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