Machine learning is all about automating the development process for analytical models. One way to extend the use of machine learning is to broaden your library of machine learning algorithms. Another way is to scale your machine learning process by reducing the time required to process machine learning algorithms on […]
As technology and analytics continue to evolve, we're seeing new opportunities not only in the way that we analyze data, but also in deployment options. More specifically, real-time deployment of analytical algorithms that enable organizations to detect and respond to security threats, offer timely incentives to customers, and mitigate risk by detecting compliance […]
The post Streaming Text Analytics: Finding value in real-time events appeared first on The Text Frontier.
Double negatives seem to be everywhere, I have noticed them a lot in music recently. Since Pink Floyd sang "We don't need no education", to Rihanna's "I wasn’t looking for nobody when you looked my way". My own favourite song with a double negative is "I can't get no sleep" - Faithless. This […]
A while ago, I started this series on natural language processing (NLP), and discussed some of the challenges of computers interpreting meaning in human language based on strings of characters. I also mentioned that today’s NLP systems can do some amazing things, including enabling the transformation of unstructured data into […]
The post Behind the scenes in natural language processing: Overcoming key challenges of rule-based systems appeared first on The Text Frontier.
Is text analytics part of your current analytical framework? For many SAS customers, the answer is yes, and they've uncovered significant value by integrating this technology. As text data continues to explode in volume, SAS Event Stream Processing can be used to analyze not only high-velocity structured data, but also unstructured […]