With the tensor decomposition, we can find low-rank embeddings of sentences that capture the similarity of contextual patterns (Hosseinimotlagh and Papalexakis, 2018).
, is the embedding vector of the sentence s. We measure the similarity of two sentences i, j by Euclidean distance: , where c(r) denotes the r-th element of c. We can train a meta-learner on the generated T train .