国产纺粘针剌非织造布生产线调试中的关键问题介绍

介绍了国产聚酯纺粘针刺非织造布生产线生产调试过程中的两个关键问题，说明了调试过程关键问题的解决办法。     

面向限定领域问答系统的自然语言理解方法综述

领域无关的自然语言理解(NLU)技术在最近的十年中取得了长足的进步,然而由于基础研究与现实应用之间存在着强烈的实际需求与当前处理能力不足的矛盾,因此很多通用技术还不能在现实的问答系统中得到有效使用。针对现有的需求,开发面向领域的自然语言理解技术显得非常必要。首先对开放领域与限定领域问答系统进行了比较,并对一些典型的面向限定领域问答系统的自然语言理解技术进行了分析,然后介绍了面向限定领域问答系统的自然语言理解技术的评测标准,最后总结了目前限定领域问答系统研究存在的主要问题及未来发展方向。     

基于句法和语义信息的问句特征提取方法

在分析当前中文问答系统中问句分析技术的基础上,提出一种基于句法结构和语义信息的问题特征提取方法。利用依存句法分析出问句的主干,从语义信息角度分析问句主干从而提取出问句的特征词,并用改进贝叶斯算法进行问题分类。实验证明,该特征提取方法能提高问题分类的准确性。     

A weighted string pattern matching-based passage ranking algorithm for video question answering

Video question answering aims to pinpoint answers in response to user’s specified questions. However, most question answering technologies involve in integrating rich specific external knowledge such as syntactic parsers, which are often unavailable for many languages. In this paper, we present a new string pattern matching-based passage ranking algorithm for extending traditional text Q/A toward videoQ/A. Users interact with our videoQ/A system through natural language questions whereas our system returns three sentence-length passages with corresponding video clips as answers. We collect 45 GB Discovery videos and 253 Chinese questions for evaluation. The experimental results showed that our method outperformed six top-performed ranking models. It is 7.39% better than the second best method (language model-based) in relatively MRR score and 6.12% in precision rate. Besides, we also show that the use of a trained Chinese word segmentation tool did decrease the overall videoQ/A performance where most ranking algorithms dropped at least 10% in relatively MRR, precision, and answer pattern recall rates.     

海安方言的“可VP”句式

本文描绘和分析了存在于海安方言中的“可ＶＰ”问句在疑问词、疑问句式、疑问焦点及停顿等方面不同于一般方言的特殊性,并以《西游记》、《红楼梦》等名著中的例子进行参证。最后,指明这种句式是非问的性质。     

Semantic passage segmentation based on sentence topics for question answering

We propose a semantic passage segmentation method for a Question Answering (QA) system. We define a semantic passage as sentences grouped by semantic coherence, determined by the topic assigned to individual sentences. Topic assignments are done by a sentence classifier based on a statistical classification technique, Maximum Entropy (ME), combined with multiple linguistic features. We ran experiments to evaluate the proposed method and its impact on application tasks, passage retrieval and template-filling for question answering. The experimental result shows that our semantic passage retrieval method using topic matching is more useful than fixed length passage retrieval. With the template-filling task used for information extraction in the QA system, the value of the sentence topic assignment method was reinforced.     

k-best MIRA和动态k-best MIRA

MIRA(Margin Infused Relaxed Algorithm)是一种超保守算法,在分类、排序、回归等应用领域都取得不错成绩.文中在传统MIRA算法基础上进行改进,提出k-best MIRA(K-MIRA)与动态k-best MIRA(DK-MIRA)算法.这两种算法能够根据学习进程自动调整优化约束条件,从而提高算法的收敛速度与性能.将K-MIRA与DK-MIRA用于定义类问题回答中的句子排序任务,取得较为满意的实验结果.     

谈谈高层建筑电气设计的主要内容及有关问题

建筑越来越多，高层建筑电气设计质量如何保证？高层建筑的主要内容及有关问题有哪些？本文根据多年对建筑电气设计经验结合规范做了初步探讨。     

基于产品建模的评论问题生成研究

问题自动生成是自然语言处理领域的一个研究热点,旨在从文本中生成自然问句.随着电子商务的不断发展,网络上产生了大量关于产品的评论.面对海量的评价信息,如何快速挖掘产品信息相关的关键评价,从而生成与产品各个层面息息相关的问答数据具有极大的研究价值,这对商家和顾客都具有极大的意义.现有的问题生成模型大多针对阅读理解类型等长文...