Unlike the traditional model in which words usually represent as one-hot vectors and are independent with each other, vector space models reveal the relationship and capture the intuition among words which different or similar to others along a variety of dimensions (Mikolov et al., 2013).
embeddings considering only at word level is usually not good for rare words as discussed above and we introduce character-level embedding to enhance the current word embedding.