Christina is a Sales Consultant at SAS Institute specializing in Text Analytics and Social Media Analysis. Her background is in primary market research and social media/Voice of Customer analysis, spanning all industries and all phases of a project lifecycle. Prior to joining SAS in 2010, she managed the Business Analyst group at Cymfony (a Kantar Media company, now merged with Visible Technologies).
There is tremendous value buried text sources such as call center and chat dialogues, survey comments, product reviews, technical notes, legal contracts... How can we extract the signal we want amidst all the noise?
Amidst the growing popularity of modern machine learning and deep learning techniques, one of the biggest challenges is the ability to obtain large amounts of training data suitable for your use case. This post discusses how the analytical approach for Named Entity Recognition (NER) can help.
