The first text analytics product SAS released to the market in 2002 was SAS® Text Miner to enable SAS users to extract insights from unstructured data in addition to structured data.  In 2009, in quick succession, SAS released two new products:  SAS® Enterprise Content Categorization and SAS® Sentiment Analysis.  These products filled niches that SAS® Text Miner did not address: namely tools for people to build and support rule-based taxonomies:  SAS® Enterprise Content Categorization for categories and concepts, and SAS® Sentiment Analysis for tone, or sentiment.

We soon learned that there was overlap between the needs of those writing rules for building taxonomies and those wanting to use SAS® Text Miner to learn or discover relationships in the data.  But alas, the three products did not have an easy mechanism to communicate between them.  One thing we did implement to support integration was to enable the import of concepts built in SAS® Enterprise Content Categorization into the Text Parsing node in SAS® Text Miner.  With this we provided limited communication; much like having an interpreter between two people not speaking the same language.

We learned from this and created SAS® Contextual Analysis, which was first released two years ago.  This product allows users to build rules for concepts and categories within the interface, but also create topics and use machine learning techniques to automatically create category rules.   SAS Contextual Analysis has been hugely successful with users: but we have also found that SAS users can benefit from both SAS Text Miner and SAS Contextual Analysis.  SAS Text Miner provides more flexibility to the experienced user and can be used to build predictive models using not just text, but all the other structured data available.  However, it is a tool that requires more analytical sophistication from users than SAS® Contextual Analysis.

So, many customers use both products.  But they really want them to talk to each other.  If you are such a customer, we now have a solution for you.  We are now providing a downloadable SAS Enterprise Miner node that you can utilize in any project to pull in the categories, concepts, and sentiment score code from a model built in SAS Contextual Analysis, and utilize them in exploration, clustering, or predictive modeling in the SAS Enterprise Miner / SAS Text Miner interface easily.

>What?  Your license for SAS Contextual Analysis is on a different machine than your license for SAS Text Miner?  No problem, included in the documentation is a convenient way to copy the SAS Contextual Analysis model files to your SAS Text Miner installation.

Check out the new node, installation documentation, and Users Guide in this zip file. And take a look at a Text Analytics Community posting that gives more detail including the documentation, if you want to look at that before downloading the node.

Of course, we must add some “small print”:  This node is provided as experimental at this time, so is not directly supported by SAS Technical Support.

Thanks for tuning in, and let me know your experience with the node!