Digimind Categorizer
White Paper
Objectives, operating methods and advantages of automated categorization within competitive intelligence activities
Download : "Digimind Categorizer : Product Sheet"
Key Benefits
- Time-saving
- Monitor more information
- Focus on analysis
- Harmonize classification
- Facilitate publication
Objective
Monitoring large volumes of information can sometimes mean that it is impossible to read all the information identified by the CI solution. Digimind Categorizer uses an automatic categorization technology which can detect major themes and file the alerts.
How it operates
Digimind Categorizer’s first step is to build up a learning database using a body of documents filed in taxonomy formation. For example, this learning database will be based on the body of documents making up Digimind Evolution.
For each new item of information presented to it, Digimind Categorizer automatically identifies the language used, then applies a number of preliminary linguistic processes (lemmatization, stemming, deletion of blank words, calculation of repetition, etc.). It then uses algorithms derived from Support Vector Machines (SVM) in order to categorize the information.