Text classification
Text classification assigns text to predefined categories. Categories and the handling of ambiguous messages must fit the task.
Assign messages to defined categories
Text classification assigns a text to one or more categories. Rules or trained models can be used. Its task is assignment; a freely written response is not necessarily required.
In a fictional inbox, messages should be routed to delivery or invoicing. “The goods are missing and the invoice amount is wrong” concerns both areas. Before deployment, decide whether multiple categories are allowed or the message goes for joint clarification.
Categories must follow the work's purpose. Sentiment analysis answers a different question, such as whether a message sounds angry. That alone does not identify the team that should handle it. Also check messages that fit no category rather than assigning them to a team without a suitable basis.
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Related terms
- Artificial intelligenceArtificial intelligence covers methods such as language processing and pattern recognition. Suitability is assessed against a specific task.
- Confidence scoreA confidence score assesses a model prediction according to a particular method. It does not grant business approval.
- Model cardA model card documents an AI model’s purpose, foundations, evaluation conditions and known limitations for a particular version.
- AI readinessAI readiness concerns the foundations of an AI project: objectives, usable data, skills, responsibilities and an operating workflow.
- Context engineeringContext engineering prepares information for individual model calls: relevant instructions, messages, sources and current states.
- Anomaly detectionMethods that flag unusual observations relative to a defined reference or a learned pattern.
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