• On feature selection, document frequency was combined with mutual information, and performance was improved.

    特征选择的方法上,结合了文档频数和互信息量,并对他们进行了改进。

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  • However, because the method of DF only USES document frequency to scale the distinguish capacity, we find it has two disadvantages.

    但是通过分析我们发现,由于仅仅使用文档频率来衡量特征的区分能力,文档频率方法存在两个问题。

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  • Still, the mathematical models used to rank results are usually some variation of the common term-frequency/inversed document frequency model, which is well-mapped territory.

    尽管如此,用于排序结果的数学模型通常是常用的词频/倒排文档频率模型的变体,而对于这种模型,已有很好的研究基础。

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  • The comprehensive method firstly used the new document frequency to select features to filter out some terms, and then employed the attribute reduction algorithm to eliminate redundancy.

    该方法首先利用新型文档频进行特征初选以过滤掉一些词条,然后利用所提属性约简算法消除冗余。

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  • To overcome the shortage of information gain in text categorization, this paper proposes a method of feature reduction based on the relative document frequency balance information gain (RDFBIG).

    针对文本分类中信息增益降维方法的不足,提出了一种基于相对文档频的平衡信息增益(RDFBIG)降维方法。

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  • This is similar to what is described in "Maximize the frequency of your lookups," and it prevents the keyword drop-down list from performing the lookup if the document is in read mode.

    这与“使查找频率最小化”中描述的内容相似,并且在文档处于读模式时它可防止关键字下拉列表执行查找。

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  • Other cache objects have configurable update Settings, and their update frequency is set by the Document Manager administrator.

    其他缓存对象具有可配置的更新设置,它们的更新频率由DocumentManager管理员设置。

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  • The create index command establishes the text index infrastructure by defining the text index attributes, such as update frequency, a document format, an index directory, and so on.

    createindex命令定义文本索引属性,比如更新频率、文档格式、索引目录等等,从而建立文本索引基础设施。

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  • An indexing engine, which is responsible to statistically analyze the plain text (derived from the binary document) and compute a list of tokens, sorted by frequency.

    索引引擎,它负责在统计层面上分析纯文本(由二进制文档派生而来),然后计算令牌的列表,按使用频率排序。

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  • rank: A value that specifies the position of the document in the results, based on the frequency of the searched words.

    rank:基于搜索词的频率指定结果中文档的值。

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  • The paper extracts the text features based on a method of word co-occurrence frequency, which is related to the semantics of document.

    本文基于词的同现频率的方法对文本的特征进行提取,涉及了文档的语义。

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  • On the basis of the frequency one article is quoted, we propose the concept importance of document and apply it to the ordering of retrieval results based on content.

    本文应用一篇文章的被引用信息提出了文献的“重要性”的概念,并将它应用到基于内容的检索结果的排序中。

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  • In order to solve the greatly dimension of word frequency and sparse matrix, this paper proposes a multi-document summarization method based on sub-topics area partition.

    为解决词频矩阵的词频维数过大和矩阵过于稀疏的问题,提出一种子主题区域划分的多文档自动文摘方法。

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  • In order to solve the greatly dimension of word frequency and sparse matrix, this paper proposes a multi-document summarization method based on sub-topics area partition.

    为解决词频矩阵的词频维数过大和矩阵过于稀疏的问题,提出一种子主题区域划分的多文档自动文摘方法。

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