Make sense of large amounts of data
Content classification
The problem
There is a vast amount of data that can be used to support an organization's decisions. This data can be internal, from years of data collection, or external, produced by users, public organizations and other businesses. Mannually sorting it or trying to understand it is no longer an option. Thanks to machine learning techniques we are able to extract information, pinpoint to the important topics and concepts.
Text classifier
Given a text and a taxonomy / classification scheme, classify every document and assign a type according to the taxonomy/scheme.
Innovation Extraction
Given a text and an innovation taxonomy (optional), segment the text into sections and classify every sentence – if it conveys an innovation statement and what type of innovation
Topics in rare diseases research
Analyse scientific publications in the health domain and identify topics in rare diseases.
-
Innovation Extraction
Given a text and an innovation taxonomy (optional), segment the text into sections and classify every sentence – if it conveys an innovation statement and what type of innovation
-
Identify topics for rare diseases
Analyse scientific publications in the health domain and identify topics in rare diseases.
