Taxonomy is a semantic logic tree that allows you to classify or filter textual data on different search criteria. It’s a great way to monitor and perform "root-cause analysis" on your data to analyze existing patterns and emerging issues. Signals enables users to generate multiple-nested Boolean strings to perform text analytics. It employs auto-categorization and taxonomies to achieve relatively high quality automated indexing results.
While Taxonomy is good for Monitoring trends, Signals also emphasizes on the A.I. based Deep Learning to help discover new topics and emerging themes from your data. Leveraging on both Taxonomy and Deep Learning , Signals will help you extract the maximum insights from your textual inputs. More on the Signals Deep Learning, please read "How does Signals Process Textual Data?"