CASIA OpenIR  > 毕业生  > 硕士学位论文
Thesis Advisor戴汝为
Degree Grantor中国科学院自动化研究所
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
Keyword自然语言处理 句子分析 人工神经网络 Natural Language Processing Sentence Analysis Artificial Neural Networks
Abstract在人工智能领域,自然语言处理一直是最为关注的研究问题。我们选择了 中国古代文学形式的一种-春联作为研究对象,计算机春联生成研究不仅包括 自然语言处理的内容,还涉及到计算机艺术的内容,因此我们希望能同时结合 语言对思维范畴作一些探讨。 本文主要研究特定论域中的句子分析方法,句子分析包含两方面的内容, 一要分析出句法结构,同时还要求获取句子中较深层的语义关系。对于汉语这 种语法规则不完备而更强调语义的语言,应该兼顾句法和语义分析,因此本文 的研究重点放在句法与语义相结合的句子分析方法上。 在符号框架之下,我们提出了一种句法与语义并存交互的句子分析方法, 该方法模拟人对语言的认知过程,它有两个主要特点:一、该方法逐词处理句 子,同时自主地利用句法与语义信息;二、语义与句法模块交互作用,指导对 方的处理过程。该方法的分析能力较强,且适应性较强,可以解决句子中存在 的歧义问题及不确定现象,并且能获取句子较深层的语义关系。 考虑到神经网络的学习功能强、鲁棒性好等特点,我们将其用于对联句子 分析。通过人工神经网络,句法与语义信息能暗含地结合在一起,存储于网络 之中。我们将BP网络模型和SRN网络模型成功地用于判断对联句子语法及语 义上的合法性,并提出了基于SRN的下联选词方法,该方法有效地结合了空域 信息和时域信息。 本文还讨论了符号主义方法与连接机制方法的集成问题,阐述了计算机春 联自动生成系统中所用到的不同层次的集成机制,并给出了整个系统框架。
Other AbstractIn the field of Artificial Intelligence Natural Language Processing is one of the main research problems. We choose Chinese old literature form Chunlian as research object. Chulian auto generation system includes not only the work in NLP, but also some work in Computer Arts. So we hope that through combining human natural language we could do some research on human thinking. This thesis is mainly focused on sentence analysis. Sentence analysis includes two aspects, firstly, analyzing and getting syntactic structure; at the same time, obtaining deeper semantic relationship in sentence. As to Chinese, its grammar system is not as complete as that of English, and the interface between the syntax and the semantics is comparatively indefinite, thus the words in Chinese language emphasize the semantics more than the syntactic function. So the thesis pays more attention on the analysis approaches combining syntactic analysis and semantic analysis. In this thesis, we propose the interactive boot based approach (IBB), which is similar to human beings' pattern of language behavior and has two main points. First, the approach processes the sentence word for word, using the syntactic and semantic information autonomously. Second, the semantic and syntactic modules interactively guide each other's process. In order to make this model similar to human beings, we choose ATN Grammar to design a syntax processor. The semantic processor is based on the concept combination. The processing ability of this approach is very good. It can resolve the ambiguity in some sentences and get deeper semantic relationships. 'Considering the advantages of Neural Networks such as their strong learning ability, nice robustness, and so on, we apply them in sentence analysis. By neural networks, syntactic information and semantic information are combined indefinitely and stored in the networks. BP and SRN neural networks are successfully applied in distinguishing between legal and illegal sentence based on syntax and semantics. In additional, we propose a word choosing approach based Simple Recurrent Network. In the thesis, we also discuss some problems in the integration of symbolic system and connectionist system and introduce the integration methods used in our system. The whole frame of our system is also presented.
Other Identifier524
Document Type学位论文
Recommended Citation
GB/T 7714
华璟. 特定论域中汉语句子分析的研究[D]. 中国科学院自动化研究所. 中国科学院自动化研究所,1999.
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