基于双向LSTM网络的不确定和否定作用范围识别

不确定和否定信息抽取是自然语言处理领域中的重要任务和研究热点.针对不确定和否定作用范围识别任务,本文提出了一种基于两层双向LSTM神经网络的作用范围识别方法.首先,对于从线索词到达词语的句法路径,本文使用第一层双向LSTM神经网络从中学习到有用特征.接着,本文将词法特征与句法路径特征一起组成当前词语的特征表示.最后,本文将作用范围识别问题看作序列标注任务,利用第二层双向LSTM神经网络界定当前线索词的作用范围.实验结果表明,本文提出的模型优于其它神经网络模型,并在BioScope生物医学语料上取得了良好性能.其中,在Abstracts子语料上的不确定和否定作用范围识别精确率分别达到86.20%和80.28%.     

基于大规模语料库的高频汉字串互信息分布规律分析

基于互信息的词典构建和自动分词是典型的基于统计的中文信息处理技术。通过计算大规模中文文本语料库的高频二字串、三字串、四字串的互信息发现:第一,高频词的互信息并不是很高,词和短语之间的互信息分布不存在明显界限;第二,高频无效汉字串的互信息与词和短语的互信息也没有明确界限,词、短语、无效汉字串互信息的夹杂分布,使得仅凭汉字串的互信息或频率很难高效地自动标注词、短语以及无效串。以上规律说明:单纯依赖对大规模真实文本语料库进行统计来实现高效的中文词典构建、自动分词处理等会面临极大挑战。     

基于Corpus库的词语相似度计算方法

构建了一个语义关联库，称为Corpus库，该库使用词语空间乖关系空间结构化地存储了词语和其上下文之间的统计信息，并通过阅读大量的预料数据来训练其相关数据。详细介绍了Corpus库的训练方法，并对训练过程中出现的大量关系提出了裁剪方案。在此基础上，通过构建词语的上下文关系向量提出了一种词语相似度算法。实验证明这是一种有效的对词语相似度进行计算的方法。     

语料库技术驱动下的大学英语教材评价分析——《21世纪大学英语读写教程》分析

教材设计的科学性是影响大学英语教学质量的重要因素,对教材的科学评定有助于教材的改进以及教师教学策略的调整。本文作者利用语料库技术,从词汇层面对《21世纪大学英语读写教程》（全4册）进行了多维度分析,观测了包括用词多样性、和《大学英语四级考试大纲》要求的呼应程度、对学生自学能力培养的关注度、题材多样性等多种要素,发现了问题并提出了建设性的应对策略。     

Application of Genetic Algorithm in unit selection for Malay speech synthesis system

Corpus based speech synthesis can produce high quality synthetic speech due to it high sensitivity to unit context. Large speech database is embedded in synthesis system and search algorithm (unit selection) is needed to search for the optimal unit sequence. Speech feature which served as target cost is estimated from the input text. The acoustic parameters which served as join cost are derived from mel frequency cepstral coefficients (MFCCs) and Euclidean distance. In this paper, a new method which is Genetic Algorithm is proposed to search for optimal unit sequence. Genetic Algorithm (GA) is a population based search algorithm that is based on the biological principles of selection, reproduction, crossover and mutation. It is a stochastic search algorithm for solving optimization problem. The speech unit sequence that has minimum join cost will be synthesized into complete waveform data.     

几何命题处理中的中文分词技术

如何将自然语言表述的初等几何命题自动转化为计算机可理解的作图语言是自然语言处理中的空白,也是实现教育软件人机交互的难点.而中文分词是自然语言处理的第1步,分词结果直接影响后期的处理工作.该文通过对几何范围内的受限语言的研究,建立了有效可行的语言理解模型,完成了词素的切分和词性标注,并在程序上得以实现.     

基于树库的汉语依存句法分析

旨在探索利用语言学手段来提高句法分析精度的可能性.采用MaltParser和自建的汉语依存树库进行相关汉语依存句法分析实验.通过对句法分析结果的分析,找出影响句法分析精度的主要因素,并据此对树库中处理某些语言结构的方式进行修改.然后再对得到的句法分析数据进行进一步分析,以确定所用方法的有效性.结果表明,无标记依存句法分析精度提高了5.5%,有标记依存句法分析精度提高了7.5%.     

热风法絮片的工艺设计

介绍了热风法絮片的主要品种和常见工艺流程 ,通过对热风固结工艺和絮片原料的探讨 ,指出热风法絮片的工艺设计关键在于主体纤维、热粘合纤维的选配和热风固结工艺的制定     

On the Competitive Theory and Practice of Online List Accessing Algorithms

Abstract. This paper concerns the online list accessing problem. In the first part of the paper we present two new families of list accessing algorithms. The first family is of optimal, 2-competitive, deterministic online algorithms. This family, called the MRI (MOVE-TO-RECENT-ITEM) family, includes as members the well-known MOVE-TO-FRONT (MTF) algorithm and the recent, more ``conservative' algorithm TIMESTAMP due to Albers. So far MOVE-TO-FRONT and TIMESTAMP were the only algorithms known to be optimal in terms of their competitive ratio. This new family contains a sequence of algorithms { A(i) } <sub>i \geq 1</sub> where A(1) is equivalent to TIMESTAMP and the limit element A(∈fty) is \mtf. Further, in this class, for each i , the algorithm A(i) is more conservative than algorithm A(i+1) in the sense that it is more reluctant to move an accessed item to the front, thus giving a gradual transition from the conservative TIMESTAMP to the ``reckless' MTF. The second new family, called the PRI (PASS-RECENT-ITEM) family, is also infinite and contains TIMESTAMP. We show that most algorithms in this family attain a competitive ratio of 3. In the second, experimental, part of the paper we report the results of an extensive empirical study of the performances of a large set of online list accessing algorithms (including members of our MRI and PRI families). The algorithms' access cost performances were tested with respect to a number of different request sequences. These include sequences of independent requests generated by probability distributions and sequences generated by Markov sources to examine the influence of locality. It turns out that the degree of locality has a considerable influence on the algorithms' absolute and relative costs, as well as on their rankings. In another experiment we tested the algorithms' performances as data compressors in two variants of the compression scheme of Bentley et al. In both experiments, members of the MRI and PRI families were found to be among the best performing algorithms.     

基于语料库的关联词识别方法

关联词语的出现在汉语文章中占有很大的比重,它们可以在复句分析中起到非常重要的作用。该文主要讨论如何在语料库中提取反映关联词语用法的各种特征信息,再通过数据挖掘算法将这些信息整理为关联词语的知识库,作为关联词识别的依据,并对有歧义的关联词语提出了基于决策树的消歧方法。最后,通过开放测试证明了该方法的有效性。