Persona-Aware Tips Generation
Table 5. Ablation experiments on the dataset Home. R-* represents the F1-Measure of ROUGE-*.
['[BOLD] System', '[BOLD] R-1', '[BOLD] R-2', '[BOLD] R-L', '[BOLD] R-SU4']
Considering that we design various of components to tackle the corresponding problems of our task, and different components play different roles on our framework. In order to demonstrate the necessity and the performance of each component, we conduct the ablation experiments on the dataset “Home”. Recall that “A” denotes the aVAE model , “M” represents the persona memory and the Pointer Networks, and “D” represents the tips quality discriminator DTips. It is obvious that persona modeling based on aVAE (A) can improve the tips generation performance. The persona memory and Pointer Networks (M) are very helpful to the effectiveness of our framework. The tips quality discriminator (D) can also contribute to the better performance. Among all the components, aVAE (A) as well as the persona memory and pointer network (M) contribute more to the improvements of the performance.