首页|Reports on Computational Intelligence Findings from Ningbo University Provide New Insights (Semantic Similarity Analysis via Syntax Dependency Structure and Gate Recurrent Unit)
Reports on Computational Intelligence Findings from Ningbo University Provide New Insights (Semantic Similarity Analysis via Syntax Dependency Structure and Gate Recurrent Unit)
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NETL
NSTL
Fuji Technology Press Ltd
Fresh data on computational intelligence are presented in a new report. According to news reporting from Zhejiang, People's Republic of China, by NewsRx journalists, research stated, “Sentences are composed of words, phrases, and clauses. The relationship between them is usually tree- like.” Our news correspondents obtained a quote from the research from Ningbo University: “In the hierarchical structure of the sentence, the dependency relationships between different components affect the syntactic structure. Syntactic structure is very important for understanding the meaning of the whole sentence. However, the gated recursive unit (GRU) models cannot fully encode hierarchical syntactic dependencies, which leads to its poor performance in various natural language tasks. In this paper, a model called relative syntactic distance bidirectional gated recursive unit (RSD-BiGRU) is constructed to capture syntactic structure dependencies. The model modifies the gating mechanism in GRU through relative syntactic distance. It also offers a transformation gate to model the syntactic structure more directly. Embedding sentence meanings with sentence structure dependency into dense vectors.”
Ningbo UniversityZhejiangPeople's Republic of ChinaAsiaComputational IntelligenceMachine Learning
NETL
NSTL
Fuji Technology Press Ltd
