Learning-based approaches alone, or combined with lexicon-based methods, usually produce state-of-the-art (SOTA) performance (Mudinas et al., 2012;Zhang et al., 2018), and thus are widely used nowadays.
learning-based methods usually demand a large amount of annotated data to train models, which has become one of the performance bottlenecks.