Building a Text Analytics Platform

Text analytics (text mining, noun phrase extraction, auto-categorization, auto-summarization, and social media or sentiment analysis) is becoming essential to any field that utilizes or tries to understand unstructured text. To develop both practical applications and deeper research results requires the development of a text analytics platform that incorporates the integration of all of these techniques.

The tutorial will take attendees through the entire process of creating a text analytics platform including:

The basic analytics techniques from deep learning/machine learning to sophisticated rule building and how to integrate them using a modular approach
How to make the business case, and what people and content resources are needed
An evaluation process to select the right text analytics software for your organization
An iterative development process that combines entity and fact extraction with categorization and sentiment analysis to add depth and intelligence to all the components
The range of types of applications that can be built with text analytics from advanced expertise applications to new uses of social media

Tom Reamy is currently the Chief Knowledge Architect and founder of KAPS Group [http://www.kapsgroup.com], a group of knowledge architecture, text analytics, and taxonomy consultants. He has 20 years of experience in information projects of various kinds. He has published a number of articles in a variety of journals and is a frequent speaker at knowledge management, taxonomy, and text analytics conferences.

For the last 10 years, his primary focus has been on text analytics, helping clients select the best text analytics software, as well as doing text analytics development projects that include applications such as call support, voice of the customer, enterprise search, and content management.

When not writing or developing text analytics projects, he can usually be found at the bottom of the ocean in Carmel, photographing strange critters.