In the original SCL as we mentioned earlier, the final classifier is trained on the extended features (x, w * x).
in table 1, we give some of the pivot features with English English Pivot Features "poor quality", "not buy", "easy use", "very easy" "excellent", "perfect", "still very", "garbage", "poor", "not work", "not to", "very comfortable" Chinese Pivot Features wanmei(perfect), xiaoguo hen(effect is very...) tisheng(improve),feichang hao(very good), cha(poor), shushi(comfortable), chuse(excellent)  Data sparseness is a common problem in NLP tasks.