Leverage a standalone text mining software application to prioritize documents for expert review.
Easily and efficiently analyze literature
Using advanced algorithms from the domains of natural language processing and machine learning, DoCTER greatly improves efficiency in tasks that involve large volumes of text.
Classify and cluster all types of documents with flexible text analytics
Clustering with seeds takes the guesswork out of prioritizing documents—such as abstracts from scientific literature—and generates unbiased forecasts of retrieval accuracy.
Apply keyword-based filters to large bodies of text
DoCTER assigns a reference to a single cluster, providing a topic signature (i.e., set of keywords) for analyzing large bodies of text. Subject matter experts review keywords and assign priority levels to every cluster.
Achieve desired levels of precision and recall
DoCTER is designed to optimize for precision, recall, or F-1 score based on user selections.