【摘 要】
：
Previous researches on event relation classification primarily rely on lexical and syntactic features.In this paper,we use a Shallow Convolutional Neural Network(SCNN)to extract event-level and cross-
【机 构】
：
Provincial Key Laboratory of Computer Information Processing Technology,Soochow University,Suzhou,Ch
【出 处】
：
第十五届全国计算语言学学术会议(CCL2016)暨第四届基于自然标注大数据的自然语言处理国际学术研讨会(NLP-NABD
论文部分内容阅读
Previous researches on event relation classification primarily rely on lexical and syntactic features.In this paper,we use a Shallow Convolutional Neural Network(SCNN)to extract event-level and cross-event semantic features for event relation classification.On the one hand,the shallow structure alleviates the over-fitting problem caused by the lack of diverse relation samples.On the other hand,the utilization and combination of event-level and cross-event semantic information help improve relation classification.The experimental results show that our approach outperforms the state of the art.
其他文献
高考阅读理解选择题是基于背景材料,通过对材料的“理解”从多个选项中选出最佳选项.由于提供的背景材料相对较短且关键信息极具隐藏性,答案可能无法在背景材料中直接找到.因此,如何从背景材料中挖掘信息并与选项进行相关性分析是解答该类问题的关键,而句子级的语义相关性分析是背景材料与选项相关性分析的基础.本文通过对大量高考科技文文意理解类选择题进行分析,提出基于多维度投票算法(Multi-Dimension
研究基于矩阵分解的词嵌入方法,提出统一的描述模型,并应用于中英跨语言词嵌入问题.以双语对齐语料为知识源,提出跨语言关联词计算方法和两种点关联测度的计算方法:跨语言共现计数和跨语言点互信息.分别设计目标函数学习中英跨语言词嵌入.从目标函数、语料数据、向量维数等角度进行实验,结果表明:在中英跨语言文档分类中以前者作为点关联测度最高得到87.04％的准确率;在中英跨语言词义相似度计算中,后者作为点关联测
统计机器翻译模型,特别是基于句法的翻译模型,其翻译单元在保留足够的翻译信息以及翻译单元在翻译新句子时的泛化能力上始终存在着一个平衡.神经网络被成功用于统计机器翻译模型中的调序和语言生成中.本文提出了一个新颖的基于神经网络的句法翻译规则生成器——依存边转换翻译规则生成器(DETG),它利用一条转换翻译规则的源端以及源端的上下文作为输入,以依存边转换翻译规则的目标端作为输出.它不仅保留了依存边——这种
Most researches to SRL focus on English.It is still a challenge to improve the SRL performance of other language.In this paper,we introduce a two-pass approach to do Chinese SRL with a Recurrent Neura
In this paper,we propose a neural graph-based dependency parsing model which utilizes hierarchical LSTM networks on character level and word level to learn word representations,allowing our model to a
In order to explore a practical way of improving machine translation(MT)quality,the error types and distribution of MT results have to be analyzed first.This paper analyzed English-Chinese MT errors f
For the difficulty of marking Vietnamese dependency tree,this paper proposed the method which combined MST algorithm and improved Nivre algorithm to build Vietnamese dependency treebank.The method too
Traditional Mongolian Unicode Encoding has serious problems as several pairs of vowels with the same glyphs but different pronunciations are coded differently.We expose the severity of the problem by
Unlike previous Mongolian morphological segmentation methods based on large labeled training data or complicated rules concluded by linguists,we explore a novel semi-supervised method for a practical
As a fundamental step in biomedical information extraction tasks,biomedical named entity recognition remains challenging.In recent years,the neural network has been applied on the entity recognition t