We finished Part One of this blog post with a simplified example to demonstrate how one might be able to measure document similarity across a given corpus using a document-term matrix as a starting point. Let’s now turn back to R and our larger sample … Continue reading →

Near-duplicate identification is one of the more common textual analytics tools used in eDiscovery. Not to be confused with document deduplication, which relies on hash values, near-duplicate identification calculates document similarity based off textual content. For example, if you had … Continue reading →