Reviewing documents with conceptual indexes in Relativity

When a Relativity admin creates a conceptual index, it will enable five different means of reviewing documents in a workspace to be performed.

1. Categorization sets can be created that use a set of example documents to find conceptually similar documents.

2. You can create clusters of conceptually similar documents without the same user input required with categorization. A few documents can be selected without assembling sets of example documents, or defining categories.

3. Concept searching can be run simply by selecting a block of text and searching across the workspace for documents with similar conceptual content.

4. Keyword expansion will find terms that are conceptually related to a selected term.

5. In the document viewer, you'll be able to select 'Find Similar Documents' to find documents related to the one you are reviewing.

Regex to Remove Relativity Numbering on Downloaded PDFs

Relativity has an annoying habit of appending numbers to the beginning of PDFs that you download from a workspace. So, files can be named with either a 1, 2, or 3 digit number followed by an underscore, and the document identifier or field selected to name the file. E.g.:

7_ABC002276411

17_IBM080414121

134_GE0005425444

Using Bulk Rename Utility you can use this regular expression search to remove the numbering, so the files are only named with the Bates numbers:

([0-9]{1}_|[0-9]{2}_|[0-9]{3}_)(.*)

In the replace box simply enter:

\2

The search for the numbers with the underscore are separated in parentheses from the second part also in parentheses which searches for any number of characters.

Dealing with large Relativity workspaces on SQL Server

Large Relativity databases can either be cached in active memory, or bring up records with high I/O throughput (data transfer speed in megabytes per second) from storage. A SQL Server table for a Relativity workspace will take up approximately 50 GB of disk space for a million documents. The SQL Server has RAM limits - the 2016 edition is limited to 128 GB of RAM. Caching the database in active memory will lead to be better performance. This is one of the key reasons why an admin may separate productions from a single case into multiple workspaces.

Hardware called Fast Track Data Warehouse can be used to provide the necessary I/O throughput if an entire dataset cannot be cached, but it is expensive and difficult to implement. It is also possible to store SQL's TempDB system on solid state or flash drives. TempDB is the system database of SQL Server which stores tables and indexes.