Machine Learning in eDiscovery Upstream

Machine Learning in eDiscovery Upstream: eDiscovery Trends

Sentiment analysis & auto classification are not new to eDiscovery, but Veritas discusses how to apply that machine learning in eDiscovery upstream!

The article (Machine Learning in eDiscovery Upstream: Sentiment Analysis & Classification, written by Irfan Shuttari and available here) discusses how in this era where the global data sphere is expected to reach 175 zettabytes by 2025, it has never been more important for organizations to understand their data as early as possible.

Two machine learning tools to leverage in eDiscovery further upstream are sentiment analysis and automated (auto) classification:

  • Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing (NLP) to identify and extract subjective information from source materials. It involves determining the attitude, sentiment, or emotion of a subject based on their spoken or written content. Sentiment analysis can be applied to a wide variety of data, and it can provide an organization with a wealth of information about its customers, products, brand, and even employees.
  • Automated data classification utilizes advanced algorithms and machine learning models to effortlessly organize information into predefined classes or categories without the need for manual intervention. This streamlined process uncovers patterns and extracts valuable insights from vast quantities of data rapidly and effectively. This approach commonly employs innovative technologies such as NLP and image recognition, as well as other AI and machine learning methodologies.

So, how can you apply sentiment analysis, auto classification and other machine learning in eDiscovery upstream? Check out Irfan’s article here to find out. It’s only one more click! Getting started with eDiscovery when the case or project begins is too late! 😉

So, what do you think? Are you applying machine learning techniques like sentiment analysis and auto classification? If so, when? Please share any comments you might have or if you’d like to know more about a particular topic.

Disclosure: Veritas is an Educational Partner and sponsor of eDiscovery Today

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by my employer or my clients. eDiscovery Today is made available solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscovery Today should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.


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