Rubitext simplifies Text Analytics with a set of Linguistic, Statistical, and ML techniques for Word Frequency Analysis, Pattern Recognition, Tagging/Annotation, Entity Extraction, Link & Association Analysis, Sentiment detection. It also offers features for Clustering, and various Classification techniques such as intent recommended actions.
Advantages
- High-performance text parsing includes automated part-of-speech and noun group detection, entity and multiword term identification, stemming, and synonym detection
- Term and frequency weighting can be configured from default settings
- Graphical and tabular output assesses terms and their distributions within a collection
- Predictive algorithms for text analysis with built-in feature extraction (vectorization)
- High-performance, the target-based weighting, is available for more accurate categorical target estimates
- Large-scale text data scoring enabled
- It enables you to describe and predict a target variable based on specific terms
- Results and graphs are interactively linked for easy exploration
- Clarify which terms are more meaningful to one another
- Visually assess emerging or declining terms over time, including how terms co-relation analysis
- When the target variable is time, the Profile node illustrates the trends of terms over the selected time
