Text Analytics for Product Management: the State of the Art
Companies have access to large volumes of user-generated text. It is a mostly unrealized corporate asset. Advances in AI over the past few years can leverage text to make an ~immediate~ impact on the bottom line. Text is now a first-class citizen in the product development life cycle!
If you care about any of these:
• What can you do with text? Why would you even care?
• What is the state of the art? Performance? Accuracy? Usefulness? Players?
• Can user-generated text be used to build a better product? (Yes.) How?
• Business case? Scenarios? Use cases? Danger zones?
...then you are cordially invited to this presentation.
Manuel Zahariev has a PhD in Comp Sci. from SFU (AI/NLP/Information Extraction/Dean of Grad Medal) and has spent over 25 years in tech. Over the years, in a number of product gigs, he has tried to make sense of large volumes of text and sometimes succeeded. He now runs a startup (https://anyw.ai).
https://www.linkedin.com/in/manuelz/