This document describes the basic concepts for understanding the Conversational Insights topic modeling feature.
Conversations
Topic modeling analyzes conversations. Each conversation is an interaction between a contact center agent and a user. Topic modeling uses chat or call transcripts that have been created using the Insights API.
For more information, see the
Conversations
reference documentation.
Topics
A topic is created by analyzing the key subjects from each conversation and then creating clusters of similar subjects. Topic modeling then identifies the number of distinct clusters, attempting to generate a name for each one. Names represent a topic, which in turn is represented by an Issue resource.
When topic modeling creates a set of topic names, you can review the names and the conversations it has labeled with that name. Topic modeling can also show you the snippet from the most representative conversation for a topic.
Fine tune a topic model
You can perform the following operations on your topic set. All these actions affect adjusted topic distributions.
- Modify an existing topic's name and description.
- Add a new topic.
- Remove an existing topic.
- Merge two or more topics. Conversations matched to any of the topics will be assigned to the new merged topic.
Topic models
When you use topic modeling to analyze conversations, Insights
creates a topic model. Topic models contain discovered topics and can be used
to infer topics for any conversation. From a topic model, you can generate a
report identifying the topics within the model and the names of each topic.
You can also deploy a topic model to your project, which will enable you to
infer topics in real-time
during a conversation with an end user. Topic models are represented by
issueModels resources.