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中文摘要：
开放领域的问题回答（QA）是近年来自然语言处理研究领域的一个热门研究方向．文中介绍基于模式匹配策略的问题回答系统，并对其进行深层次的性能分析与评价，讨论检索参数和训练样例数目对系统性能的影响．同时，进行t-test来检验不同因素对系统性能影响的显著性，旨在对系统实现细节有更明确的分析，更有效地提高系统性能．系统中运用自然语言处理工具，如句法分析器、实体名识别工具等，工具本身的性能也是影响QA系统性能的一个重要因素．
英文摘要：
Open domain question answering （QA） has drawn much attention from the natural language processing communities. A pattern based question answering system is introduced, and the deep performance analysis and the evaluation of the QA system are presented. The impact of parameter tuning and training set size on system performance is discussed as well. Meanwhile, the t-test results denote the significance of the performance improvement by different factors. Natural language processing tools are used in the QA system, such as the syntax parser and the named entity recognition tool. Analysis results indicate that these tools play an important role in the QA system.
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