Tag: Text Analytics

Russ Albright 0
Focusing your Text Mining with Search Queries

Recently, I have been thinking about how search can play more of a part in discovery and exploration with SAS Text Miner. Unsupervised text discovery usually begins with a look at the frequent or highly weighted terms in the collection, perhaps includes some edits to the synonym and stop lists,

Tuba Islam 0
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,

Gerhard Svolba 0
SAS Contextual Analysis: ein Selbstversuch

Erfahrungen aus einem Selbstversuch mit SAS Contextual Analysis Bitte verstehen Sie mich nicht falsch. Ich bin unseren SAS Produkten und SAS Lösungen gegenüber in keinster Weise misstrauisch! Trotzdem wollte ich die Möglichkeiten unserer neuen Lösung für Text Analytics „SAS Contextual Analysis 14.1“ auf der eigenen Haut spüren und verstehen lernen.

David Pope 0
Saving lives with big data and analytics

Big data is here to stay, whether we like it or not. Regardless of how you feel about it, it can help solve problems which simply could not be addressed without big data and advanced analytics. One area in which big data and analytics can provide huge benefits is the medical arena. In a recent

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

Machine Learning
Sascha Schubert 0
What’s new with machine learning?

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

Data Management
Leo Sadovy 0
Big Silos: The dark side of Big Data

The bigness of your data is likely not its most important characteristic. In fact, it probably doesn’t even rank among the Top 3 most important data issues you have to deal with.  Data quality, the integration of data silos, and handling and extracting value from unstructured data are still the most

Fiona McNeill 0
Seth Grimes with More on Text Analytics

Perhaps it’s the same for you - it’s getting harder to get to all the conferences I’d like to attend. One of the benefits of getting out there is a chance to learn about different perspectives in an industry. When someone has a broad perspective, particularly if they’ve been in