This Solution Provider Webinar is brought to you by DIA in cooperation with Content Analyst.

Searching for relationships across disparate collections of research documents, articles and reports can be an incredibly time-consuming and labor-intensive process. Boolean keyword searches can produce false positives and omit results that could be highly relevant if the exact search terms aren't found in a document, and laborious taxonomies can be incredibly time-consuming to build and maintain.  In addition, varying user interfaces, search capabilities, and the inability to search across content sets can dramatically inhibit productivity.

Join this informative and educational web symposium to learn about entirely new and highly secure, web-based approaches that leverage the power of machine learning technology to enable product managers and researchers to quickly discover hidden relationships and insights within and across vast, disparate collections of internal and external text-based content. See firsthand how machine learning technology can identify concepts and relationships within unstructured, text-based content, in nearly any language, without the need to build and maintain taxonomies and word libraries. See how to quickly and easily apply machine learning technology across internal research reports stored on your computer or company network or internal software applications, articles from news sources and industry journals in the Web, and open source offerings such as Wikipedia.