Detecting the topics of text fragments
Efficiently categorize and rout customer inquiries to the corresponding customer service consultant with topic detection. Topic detection scans a piece of text and determines the underlying topic, and then automatically assigns the text to a predefined category.
For example, when a customer writes My phone is not working, need help! in a chat window, topic detection analyzes and assigns the sentence to thecategory. Your application then connects the customer with the corresponding customer service consultant.
To learn more about the types of topic detection and how to create topic detection models, see the following articles:
- Comparing keyword-based and machine-learning topic detection
Pega Platform offers two types of topic detection models that you can use interchangeably, depending on your needs. Learn more about the differences between keyword-based and machine learning topic detection models and when to use them.
- Creating keyword-based topic detection models
Efficiently connect your customers with the right consultant without having to provide training data to the topic detection model. Instead, you can use a list of topic-specific keywords to train the model.
- Creating machine-learning topic detection models
Efficiently connect your customers with the right consultant by providing training data to a topic detection model.
- Best practices for creating categorization models
Use categorization analysis to assign labels to text. In Pega Platform, you can categorize text into topics, sentiments, and intents.
- Requirements and best practices for creating a taxonomy for rule-based classification analysis
The right classification of data in a taxonomy makes relevant information more accessible, which can have various practical applications. This information can help you address customer support requests in a timely manner or gather feedback on your products.