The objective of tensor decomposition is to find an approximationŴ of W so    where is the predefined rank parameter, and ⊗ is the outer product, namely, v r ⊗ v r ⊗ d r being a three-dimensional tensor, and With the tensor decomposition, we can find low-rank embeddings of sentences that capture the similarity of contextual patterns (Hosseinimotlagh and Papalexakis, 2018).
c = where the s-row of c is the embedding vector of sentence s. The Euclidean distance of embeddings is used to measure the similarity of two sentences.