Though still an emerging practice, automatic classification of content is gaining momentum (finally) due to recent court decisions regarding the use of predictive coding: “… in 2012, a federal district court held that ‘predictive coding’ using software trained by lawyers to identify and classify relevant documents could be substituted for lawyers manually searching for and reviewing every potentially relevant document
Big bucket retention schedules (100-150 record series/retention categories for an enterprise) are more cost effective to maintain and increase filing accuracy for both manual and automatic classification. They also make training more efficient for anyone who has to implement retention policies in ECRM systems such as IT, RM, records coordinators, information champions, or SharePoint TeamSite and site collection owners
For example, automatic classification may prevent the ability to alter or change the classifications
Now I know this is not the most exciting topic, but it is worthwhile because the role of taxonomy is becoming increasingly important to the complete search experience as well as the automatic classification of documents in various applications (see also the footnote)
True enough, but this concept assumes that there is a standard classification scheme in use by the entire enterprise; that all employees willingly classify their email messages according to it (or there is an automatic classification tool that works with more than 10 categories); and that there is actually some way to retain messages according to their assigned retention periods rather than copying them sequentially to storage media
The great news is that with newer technologies that support role-based retention categories, automatic classification, and so on, their job is getting easier
What is so cool about classification is there is an even tighter control of the quality of the automatic classification because it's much easier to toggle what is right or wrong
Metadata extraction and automatic classification can help you avoid human errors and improve search
Technology Assisted Review (TAR) is a marketing term used in the eDiscovery community to describe the process of automatic classification of documents in a so-called legal review
In lifecycle governance use cases we regularly use automatic classification technologies to classify email, documents, and files into the right categories in a global file plan and to support value-based retention policies
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