Description: building a system for automatic processing of incoming calls to the contact centre assumes the presence of a specified taxonomy, which will be used to categorize the request and then process it. When working with a large number of contact centres, you need a system for quickly analyzing dialogues and then building a taxonomy of categories for a specific contact centre.
Context: it is important for CC analysts to quickly understand what topics are included in the dialogue corpus in order to quickly automate their work. Manually dividing such cases into topics is a labour-intensive task.
Decision: a system of hierarchical clustering of contact centre dialogues is proposed, which allows creating a taxonomy of intents.
Results: Integration into the BI Department for automation of customer contact centres:
Reducing the load on the analyst to allocate automation classes by 80%.
Harmonization of taxonomy:
Reducing the time to identify a new category by 60%;
Allocation of new intents in the flow of requests with a quality of 70%.
The selection of entities and the analysis of interpretability:
Selecting named entities and filling in the client card is 10% more accurate;
Increase in the share of interpreted intents relative to the old model by 40%.
To build the model, we used:
Dialogues for multiple contact centres;
Assessor markup of paraphrases for each dataset.
Simulation result:
Model for soft hierarchical clustering of dialogues;
Final taxonomy of categories with a description;
A server-side custom application with an API interface.