Categorization: Concept-based Categorization is another way to organize your document set - you just have to know a bit about what you’re looking for first. With Concept-based Categorization, Evident will quickly identify documents within large collections that fit into one or more categories that you have previously defined. It is as simple as collecting a few dozen representative documents - or even parts of documents - that describe a given topic of interest, putting them into a category, and giving that category a name.

Evident will review every document in the collection and compare each one to the examples in your categories – when there is a correlation, it will categorize that document as belonging to that category. Often documents might fit into multiple categories, so Evident gives you a “score” showing just how well the document matched the examples. Documents that don’t fit well into any category are automatically put into an “uncategorized” group that can be addressed later.

By using Concept-Based Categorization, Evident quickly populates folders of interest with relevant documents, so your reviewers can start getting to the key issues of the case immediately.
 

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Categorization is your best option when the following conditions are present: Your case has a very large, unorganized datasets that you want to organize based upon document concepts. The case issues and categories are already known . The title or representative categories are already known. You have one or more focused example documents to represent the conceptual topic of each category
 

Dynamic Clustering: Evident offers Dynamic Clustering to organize a large number of documents all at once, in an automated way. Dynamic Clustering analyzes all of the documents in the collection and places them into a hierarchy of folders and sub-folders based on conceptual content. Finally, Dynamic Clustering applies a title to each of these folders or clusters, using terms that describe the concepts contained in them.

For a “first look” at a collection of Electronically Stored Information (ESI), Dynamic Clustering is an optimal way to identify what groups of documents may be important and which clusters can be ignored or deferred. Evident’s Dynamic Clustering is especially useful when you are unsure of what is in a collection of documents. Why waste hours of valuable time wading through virtual stacks of keyword search results - let Evident do the work for you.
 

Near Duplication: Evident identifies documents that are near duplicate. This allows reviewers to quickly cull similar or ‘like’ documents based on conceptual data. Locating near duplicate documents helps contain costs and decreases review times
 

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