Tag: text mining

Tuba Islam 4
Widening the use of unstructured data

Analyzing text is like a treasure hunt. It is hard to tell what you will end up with before you start digging and the things you find out can be quite unique, invaluable and in many cases full of surprises. It requires a good blend of instruments like business knowledge,

Jim Cox 1
Topical advice about topics, redux

In my last post, I talked about why SAS utilizes a rotated Singular Value Decomposition (SVD) approach for topic generation, rather than using Latent Dirichlet Allocation (LDA).  I noted that LDA has undergone a variety of improvements in the last seven years since SAS opted to use the SVD method.  So, the

Machine Learning
Andrew Pease 0
Towering Insights

The benefits of big data often depend on taming unstructured data. However, in international contexts, customer comments, employee notes, external websites, and the social media labyrinth are not exclusively written in English, or any single language for that matter. The Tower of Babel lives and it is in your unstructured

Dan Zaratsian 0
Streaming Text Analytics: Finding value in real-time events

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

Dan Zaratsian 0
Event Stream Processing with Text Analytics

Is text analytics part of your current analytical framework? For many SAS customers, the answer is yes, and they've uncovered significant value as a result. As text data continues to explode both in volume and the rate at which it's being generated, SAS Event Stream Processing can be used to

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