Hot Neuron LLC announces the release of version 2.3 of its Clustify(TM) software, featuring content-based e-mail threading to reduce the number of documents that must be reviewed during e-discovery.
Clustify groups related documents into clusters and identifies a "representative document" for each cluster, allowing the user to review and categorize related documents together, for greater efficiency and consistency. The user specifies the desired relationship between the documents by selecting a similarity function. The similarity function might indicate that the documents should be conceptually similar, or that they should be near-duplicates. Version 2.3 adds a similarity function aimed at grouping e-mails from the same thread together based on an analysis of the body of the e-mail, which is useful when headers aren't available. Clustify labels each cluster with descriptive keywords, providing a uniform interface for navigating the documents regardless of which similarity function the user selects.
Clustify can automatically categorize newly-added documents by using the specified similarity function to compare the new documents to the ones that have already been categorized, sometimes referred to as "predictive coding." The new version adds more control over this process. Version 2.3 also integrates with newer versions of third-party tools, and offers more options when exporting results to other systems.
"Version 2.3 provides greater flexibility while still maintaining the scalability to handle large document sets on modest hardware," according to Bill Dimm, the CEO of Hot Neuron. "The user-interface remains simple, and performs consistently across very different calculations."
By Guest Blogger: Clustify / Hot Neuron LLC
