One of the driving factors in e-discovery behind the spectacular growth in linguistic analytical tools like concept search, document clustering, and PC/TAR is the simple fact that people don’t all speak alike. I sometimes buy a grinder for lunch, while my business partner prefers subs, and a Philadelphia-based client of mine prefers hoagies. We’re all talking about the same kind of sandwich, of course (though there’s some debate over the need for lettuce), but a computer algorithm using key word search won’t necessarily make that connection unless a helpful human being has manually tied these different terms together for it. A good concept or context search engine, however, will recognize that these terms are often discussed in similar circumstances (e.g., lunch, types of cheese); it will serve up these sandwich terms together, not separately.
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