1. Adaptive2 Language Model
Hyun Goo Kang
Stanford University
CS224N Final Project

2. Domain Sensitivity People use languages very differently
Statistical NLP Models perform better when trained on the right domain of data

3. Domain Adaptive Model
Yet, we cannot simply neglect language data from the less-related domains.
Solution: Adaptive1 Model
Include all data, but weight them differently!
Given multiple domains of data, find the optimal weights of each domain to maximize our performance!

4. Domain Adaptive Model Limitation: Solution: Adaptive2 Model
In real-world, domains are not well-defined.
Solution: Adaptive2 Model
Given any mix of data, we form “domains” with document clustering techniques.
Document clustering works pretty well across domains.
Given user data (or test data), we “adapt” our model to the right domains.

5. Results

6. Results