• 过去式和过去分词的构成方法。

    Past tense and past participle of the composition method.

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  • 学习过去分词的用法:用作状语。

    Learn about the Past Participle (3) : used as Adverbial.

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  • 基于词的方法是日语分词的主流方法。

    Word-based approach is the mainstream on Japanese word segmentation.

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  • 于是就有了分词的必要。

    So there will be a participle necessary.

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  • 对分词的结果再进行综合加权处理,最终得到文档的特征概念集。

    Using the result of word segmentation we give a comprehensive feature weight calculation and we get the feature words set.

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  • 索引模块中:首先,讨论了中文分词的设计思想,选择了分词的算法。

    Index module: first of all, discuss the design method of Chinese word segmentation and choose a word segmentation algorithm.

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  • 实验表明此方法提高了分词的速度和准确性,达到了较好的分词效果。

    The paper proves that this method has improved the speed and accuracy of words segmentation, and gets the better effect of words segmentation.

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  • 为了改善合成语音的自然度,本文在传统分词的基础上提出了词的组合方法。

    In order to improve the speech naturality, the paper puts forward the combinatorial method which bases on participle.

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  • 进行高级汉字文本分词的功能模块,可以支持多种类型文本,支持停用词过滤。

    Chinese text segmentation for advanced function modules that can support multiple types of text, support for stop words filtering.

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  • 词典是中文自动分词的基础,分词词典机制的优劣直接影响到中文分词的速度和效率。

    As a basic component of Chinese word segmentation system, the dictionary mechanism influences the speed and the efficiency of segmentation significantly.

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  • 分词词典机制是影响自动分词的重要因素,而查找速度是衡量一个词典好坏的重要标准。

    The dictionary mechanism is an important factor affecting automatic word segmentation systems and the finding speed is an important criterion to determine the performance of a dictionary.

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  • 组合型歧义切分字段一直是汉语自动分词的难点,难点在于消歧依赖其上下文语境信息。

    Combinational ambiguity is a challenging issue in Chinese word segmentation in that its disambiguation depends on the contextual information.

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  • 对于海量信息处理的应用,分词的速度是极为重要的,对整个系统的效率有很大的影响。

    The rate of text participle is most important especially in applied in great information handling, and it affects the efficiency of whole system.

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  • 新词的存在使得汉语分词结果中出现过多的“散串”,在很大程度上影响了分词的准确率。

    The unrecognized new words can result in too many sequences of single characters in the segmented sentence, which decreases the segmentation precision to a remarkable extent.

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  • 针对邮件文本分词效果较差的特点,提出采用一种改进的最大匹配法来进行中文分词的方法。

    Aiming at the dissatisfied effect of Chinese word segmentation to Email texts, an improved Maximum Match Based Approach is presented.

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  • 本文利用前向神经网络的交叉覆盖算法,通过对文本进行分词的预处理后,实现文本的自动分类。

    Based on the Crossing Cover Algorithm of forward neural network, this paper realizes the automatic classification of texts after the preprocessing of the texts.

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  • 本文首次使用SVM方法来完成中文分词的任务,使用上下文窗体属性和基于规则的属性对样本进行刻画。

    Here we explore SVM for a Chinese word segmentation task, use the context attributes and rule-based attributes as the features for a sample.

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  • 单汉字标引法是在基于汉语分词的自动标引研究遇到不可克服的困难之后,而产生的一种新的自动标引方法。

    The single Chinese character indexing is a new automatic indexing method produced as automatic indexing research of Chinese word segmenting meets some difficulties that can't be overcomed.

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  • 在现阶段还没有一种很好的方法来解决中文分词的问题,本文将会提出一种面向用户兴趣建模的中文分词方法。

    Now there isn't a good enough method to solve the problem of character compartmentation. In this paper, a method to solve the problem of character compartmentation is proposed.

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  • 为扩展分词词典,提高分词的准确率,本文提出了一种基于信息熵的中文高频词抽取算法,其结果可以用来识别未登录词并扩充现有词典。

    Targeting at extending the dictionary for word segmentation so as to improve its accuracy, this paper presents a high-frequency Chinese word extraction algorithm based on information entropy.

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  • 本文首先对中文文本分词进行了介绍,在常用分词算法的基础之上设计了一种双向匹配分词算法,有效的减少了歧义词对正确分词的影响。

    In this paper, Chinese word segmentation is introduced first, and then algorithm named two-way matching term is designed, which effectively reduces the ambiguity of the Chinese words.

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  • 比如“write”一词,有该词的原形的“write”、第三人称单数的“writes”、过去式的“wrote”以及过去分词的“written”。 是把它们算为4个单词呢,还是算为1个单词?

    Should “write”, “writes”, “wrote”, “written” count as four words or one?

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  • 规则动词的过去分词以-ed结尾。

    The past participle of regular verbs ends in '-ed'.

    《牛津词典》

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