Successful Data Discovery with Taxonomies and Semantic Analysis
Watch the taxonomy webinar below.
Siloed, unstructured, language-based enterprise data is challenging to gain insights from for better decision making. Teams that combine personal and open-source approaches tend to spend more time managing their technology stack than using that knowledge to create value.
Gaining control over language assets such as documents, emails, reports, and webpages can help teams to build more efficient semantic search, intelligent applications, and customized knowledge bases. This can be done through a combination of symbolic (rules-based) and machine learning approaches to provide the highest degree of accuracy, explainability and flexibility.
Watch AI and knowledge discovery experts Christophe Aubry and Kevin Atkinson to hear several real-world natural language examples where Hybrid AI is used for successful data discovery. You will learn how to:
- Identify relevant concepts and topics by applying automatic semantic analysis
- Improve knowledge discovery and natural language applications by building your own knowledge graphs
- Automate document analysis by semantically classifying large volumes of unstructured data with taxonomies