Word-sense disambiguation identifies which sense of a word is used in a sentence. Dr. Louis Glassy explores where WSD could be used to help clarify what a given sentence means — and it’s all about context.

RISER software uses machine learning to increase the U.S. Government's ability to search against databases and watchlists for criminals and terrorists.

Enterprises benefit from turning text into data in many ways, including better business insights.

Taxonomies and ontologies allow organizations to define what is meaningful to their particular line of business and use those terms to classify content. Enterprises use the ontology and resulting classification for better search and improved workflow.

Automated text classification tends to use rulebases or machine learning, and the choice of which to use often comes down to how precise your results need to be.

Definitions of terms help us all know that we’re talking about the same things. This list is updated periodically. Feel free to suggest editions.

Though contrary to the common thought that one needs to create a whole, fully-formed, and robust model before classification, an iterative process will allow you to develop a solid taxonomy or ontology that delivers value early and frequently. Building a taxonomy is a process of discovery – you will generally not know the destination of your effort when you begin the process.

The conversation about cognitive computing and big data often is enterprise focused—how we can make better business decisions, discover new business opportunities and the like—but the projects at HLTCon highlighted a real ability to turn big data into information that can help people in need, both in the collective sense and in the individual sense. It is this kind of creative use of NLP technologies that can literally make cognitive computing smart enough to do some good.

Announcing the launch of the Cognitive Computing Consortium, a forum for researchers, developers and practitioners of cognitive computing and its allied technologies.

Learn how researchers are demystifying machine learning by making the process more transparent and the results more interpretable and usable by people.

Puns make you laugh or groan, but computers have a hard time understanding them.

The hyper-logical killing machines in movies differ greatly from the vision of a machine-aided society. Let’s compare some actions of movie robots with those that now live in our hands and on our counter tops.

Automated text classification tends to use rulebases or machine learning, and the choice of which to use often comes down to how precise your results need to be.

As a lifelong writer, reader, and analyst, I am fascinated with how we communicate with one another — even when we fail spectacularly at doing so — and I have become involved with helping computers understand us.