Tutorials

  1. To use DoCTER, users must first choose the particular function they wish to deploy from the dashboard.
  2. Text to be analyzed must be provided to DoCTER as a csv file in the appropriate format that will be uploaded from the user's computer.
  3. Additional parameters for the analysis must be specified and submitted in the browser form as prompted.
  4. Following cloud-based analysis, output will be available for download to the user's computer.
  5. Click through this tutorial for further guidance. We have created a demo dataset which can be used to test various DoCTER functions, which you can download by clicking the link below:
Input and Output File Formats
Input and Output File Formats

Overview of Input and Output file formats.

Topic Extraction (Clustering)
Topic Extraction (Clustering)

Clusters a set of documents into a user-specified number of bins. For each bin, identifies the defining topics/keywords.

Supervised Clustering
Supervised Clustering

Classifies a set of documents as relevant or non-relevant to a topic. Assigns discrete (1-6) priority scores to each document.

Machine Learning
Machine Learning

Classifies a set of documents as relevant or non-relevant to a topic. Assesses the probability of a document being relevant to the topic of interest.