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首页> 外文期刊>International Journal of Computer Processing of Oriental Languages >A Hybrid Method to Determine Inter-Clause Dependency
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A Hybrid Method to Determine Inter-Clause Dependency

机译：确定子句间相关性的混合方法

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摘要

The longer the input sentences, the worse the syntactic parsing results. Therefore, a long sentence is first divided into several clauses, and the syntactic analysis for each clause is performed. Finally, all the analysis results are merged into one. In the merging process, it is difficult to determine the dependency among clauses. To handle such syntactic ambiguity in determining inter-clause dependency, this paper proposes a hybrid method using restriction rules and Decision Trees-based machine learning. Based on restriction rules, clauses that cannot be the governor of a dependent clause are excluded from the governor candidates. Next, using Decision Trees machine learning algorithm, one clause is selected as the governor of a dependent clause. We extract various features from a clause, and analyze the effect of each feature on the performance. Experimental results show that our hybrid method outperformed both methods of using restriction rules and using Decision Trees.
机译：输入句子越长，句法分析结果越差。因此，长句子首先被分为几个子句，并对每个子句进行句法分析。最后，所有分析结果合并为一个。在合并过程中，很难确定子句之间的依赖性。为了解决在确定子句间依存关系时的这种句法歧义，本文提出了一种使用限制规则和基于决策树的机器学习的混合方法。根据限制规则，不能成为从属子句的总督的子句将从总督候选中排除。接下来，使用决策树机器学习算法，选择一个子句作为从属子句的控制者。我们从子句中提取各种功能，然后分析每个功能对性能的影响。实验结果表明，我们的混合方法优于使用限制规则和决策树的方法。

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