Inspired by Machine Reading Comprehension (MRC), we regard the product title and product attribute as 'context' and 'query' respectively, then the 'answer' extracted from 'context' equals to the attribute value wanted.
we model the contexts of title and attribute respectively, capture the semantic interaction between them by attention mechanism, and then use Conditional Random Fields (CRF) (Lafferty et al., 2001) as output layer to identify the corresponding attribute value.