Characterization inference based on joint-optimization of multi-layer semantics and deep fusion matching network.

ABSTRACT: The whole sentence representation reasoning process simultaneously comprises a sentence representation module and a semantic reasoning module. This paper combines the multi-layer semantic representation network with the deep fusion matching network to solve the limitations of only considering a sentence representation module or a reasoning model. It proposes a joint optimization method based on multi-layer semantics called the Semantic Fusion Deep Matching Network (SCF-DMN) to explore the influence of sentence representation and reasoning models on reasoning performance. Experiments on text entailment recognition tasks show that the joint optimization representation reasoning method performs better than the existing methods. The sentence representation optimization module and the improved

SUBMITTER: Zheng W 

PROVIDER: S-EPMC9044352 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature