Techniques & Methods
Variation
In NLP, variation refers to the many ways the same intent or information can be expressed in natural language. "Book a flight," "I need to fly to London," and "reserve plane tickets" all convey the same intent despite different wording.
Handling linguistic variation is essential for robust AI systems. Training on diverse paraphrases, using semantic embeddings rather than exact keyword matching, and data augmentation techniques all improve a model's ability to handle variation.
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Related Terms
Techniques & Methods
Semantic Similarity
Measure of how closely related two pieces of text are in meaning.
Core Concepts
Natural Language Understanding (NLU)
AI's ability to understand and interpret human language meaning and intent.
Techniques & Methods
Data Augmentation
Increasing training dataset size and diversity by creating modified copies of existing data.