Voice of Customer analytics seeks to transform unstructured feedback into usable data. Learn how to build an effective Voice of Customer analytics program that increases revenue and reduces churn via better-informed decision-making.
Robotic Process Automation (RPA) is moving towards larger, transformational initiatives. As part of that shift, RPA vendors must improve their natural language processing (NLP) capabilities to support trending text analytics use cases. In this article, we explore your options as an RPA vendor looking to add new text analytics and NLP capabilities to your platform.
Paul Barba explains the role of machine learning and AI in natural language processing, how to apply machine learning to solve problems in natural language processing and text analytics, and why a hybrid ML-NLP approach is best.
Robotic Process Automation (RPA) reduces costs and increases profitability by freeing workers to focus on higher-value work. This article explains how text analytics and natural language processing fit into that picture, and why RPA providers looking to add text analytics and NLP into their platform are better-off buying and integrating a solution from an established vendor.
Artificial intelligence has rendered HIPAA obsolete. As AI in healthcare becomes commonplace, data privacy, security and ethical issues are growing. We explored the uses of AI in healthcare, the ethical issues involved, and why experts are raising flags about healthcare data storage and data security practices.
Is saving money on your car insurance reason enough to trade away your privacy? We researched how automakers, insurance companies and advertisers use telematics to collect, analyze and monetize data about your driving habits, and why maybe you shouldn’t be so quick to jump on the telematics bandwagon.
It’s election season and the Lexalytics Blog once again turns its attention to current political events. This time we fed the October 2019 Democratic debate to our AI-powered NLP tool, Semantria. In this article we review many of the insights we discovered.
Instead of going for a high-risk moon-shot, here’s how to effectively integrate AI into your business to solve tangible problems. In this article, originally posted on Forbes, Lexalytics CEO Jeff Catlin keeps it clear and concise.
26 million people had already used take-home genetics testing kits by the start of 2019. But what happens to your data afterwards? We looked into it and found biotech firms, retailers, law enforcement agencies and others buying and accessing DNA data en masse.
Healthcare databases are growing exponentially. Today, healthcare providers, drug makers and others are turning this data into value by using text analytics and natural language processing to mine unstructured healthcare data and then doing something with the results. Here are some examples.