In this paper, we present a learning-based approach for enabling domain-awareness for a generic natural language interface. Our approach automatically acquires domain knowledge from user interactions and incorporates the knowledge learned to improve the generic system. We have embedded our approach in a generic natural language interface and evaluated the extended system against two benchmark datasets. We found that the performance of the original generic system can be substantially improved through automatic domain knowledge extraction and incorporation. We also show that the generic system with domain-awareness enabled by our approach can achieve performance similar to that of previous learning-based domain-specific systems.
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