Predictive Coding Is So Yesterday
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Computational linguistics and data mining are among the tools that will drive e-discovery in coming years.
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The Future of Predictive Coding
Technology-assisted review tools of the future will analyze ESI using computational linguistics without any user input to analyze ESI content, far beyond keywords, key phrases, or training sets of ESI documents subject to human error. Content analysis will allow powerful categorization of ESI based on data mining and language translation techniques.
Once categorized, users can review categories of ESI rather than any set number of ESI items (as is required by predictive coding). Human review will take place under error checking and marking consistency feedback made possible through information theory measures drawn from categories of semantic meaning. Such meaning will be determined by the content of ESI populations and not any error-prone training of predictive coding.
Because these methods analyze ESI based on each the semantic content of ESI data sets, such methods will be adaptable to a wide range of ESI content and in fact be ESI content driven. In other words, there will be no training sets—or user defined categories—for the algorithms to learn about or compare.
Read original articleTags: computational linguistics, data mining
