Intent matching

Matching algorithms

two algorithms to match intents: rule-based grammar matching and ML matching.

simultaneously attempts both algorithms and chooses the best result.

Algorithm Pros Cons
Rule-based grammar matching Accurate with a small or large number of training phrase examples.Models are updated quickly. Does not support the automated expansion entity option.
ML matching Accurate with a large number of training phrase examples. Matching is fast. Inaccurate with a small number of training phrase examples.Models are updated slowly.Less accurate than grammar matching for agents with training phrases in template mode.

Intent priority

You can set priorities for intents. When two or more intents match the same end-user expression with similar confidence scores, priority is used to select the best match. Otherwise, the confidence score for intent matching is more important than priority.

Reference

  1. Speech and Language Processing
  2. Evaluation of Intents Classification Model using Dialogflow Client Library
  3. transformers_joint_intent_classification_slot_filling.ipynb
  4. Dialogflow ES documentation
  5. sz128/slot_filling_and_intent_detection_of_SLU
  6. 如何创建一个问答对话流程