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过滤阈值
相关语句
  filtering threshold
     This system adopts a new algorithm of feature extraction and a new method to determine filtering threshold based on small webpage training sets and term-frequency statistics of corpus.
     该系统采用了一种新的基于少量Web示例网页和语料库词频统计的特征抽取算法和过滤阈值设定方法.
短句来源
  “过滤阈值”译为未确定词的双语例句
     The main work in this dissertation is to study the new algorithm of profile learning and new approval to optimize the dissemination threshold.
     本文的主要工作就是研究自适应信息过滤中提高模板准确性的学习算法和过滤阈值优化的新方法。
短句来源
     On the test step, new method was introduced to exploration the dissemination threshold.
     在模型的测试阶段,以过滤系统效能函数最优为目标,给出了探索最优的过滤阈值的新算法。
短句来源
     As a branch ofinformation filtering, text filtering relates to extensive knowledge, and it colligates a lot ofknowledge in Natural Language Comprehension、Artificial Intelligence and Knowledge Theoryetc.
     文本过滤作为信息过滤的一个研究分支,它涉及的知识范围非常广泛,综合了自然语言理解、人工智能以及知识论等领域的知识,其关键技术主要包括文本分词、文本特征向量降维、文本特征提取、用户模板和过滤阈值初始化以及机器学习等。
短句来源
     The thesis put forward a kind of percolation of adjustable stanza value (related threshold value) enactment method, user can according to need to choose to filter the accurate grade to regulate the exportation quantity of the interest web.
     论文提出了一种可调节的过滤阈值(相关门槛值)设定方法,使用户可根据需要选择过滤精确等级来调节兴趣网页的输出质量。
短句来源
  相似匹配句对
     Research on adaptive information filtering based on incremental learning and threshold optimization
     基于增量学习和阈值优化的自适应信息过滤研究
短句来源
     Filtration Technology and Facilities
     过滤技术及装置
短句来源
     Filter dewatering of hydraulic oil
     液压油过滤脱水
短句来源
     Nerve Threshold Value Detector
     神经阈值探测仪
短句来源
     Threshold Optimization with a Small Number of Samples in Adaptive Information Filtering
     自适应信息过滤中使用少量正例进行阈值优化(英文)
短句来源
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  filtering threshold
The depth filter is similar as the one we applied for plane primitives, but using the circle center's depth value as a filtering threshold.
      


Traditionally, text filtering based on support vector machine uses the vector space model to represent the text and user profile. Vector space model draws the noise into the system because it assumes that the word in the text is independent and it influences the performance of the filtering. The proposed method was based on vector support machine of semantic space in which text and user profile were represented by the semantic space. The proposed approach used the singular-value decomposition to derive a latent...

Traditionally, text filtering based on support vector machine uses the vector space model to represent the text and user profile. Vector space model draws the noise into the system because it assumes that the word in the text is independent and it influences the performance of the filtering. The proposed method was based on vector support machine of semantic space in which text and user profile were represented by the semantic space. The proposed approach used the singular-value decomposition to derive a latent semantic space. User profile and filtering threshold could been got by training the support vector machine in the semantic space. And the similarity between the user profile and new text was computed by cosine measure, after the new text was mapped into the semantic space. Experimental results show that the filtering rate of our approach can get 98.67%.

传统的基于支持向量机的文本过滤,用向量空间模型来表示文本和用户模板,向量空间模型假设特征项之间是线性无关的,该假设引入了许多因具体用词变化不定而带来的词汇噪音信息,影响了基于支持向量机的文本过滤的过滤性能。提出基于语义空间的支持向量机的文本过滤,用语义来表示文本和用户模板。该方法主要通过奇异值分解提取文本的潜在语义空间,在语义空间上训练支持向量机得到用户模板和过滤阈值,文本流上的文本映射到语义空间上,在语义空间上计算用户模板和新文本的相似度。实验表明:该方法的过滤性能可以达到 98. 67%。

Although current search engines based on keywords satisfy some users' need,they can't meet users' personalized demands for their all-purpose characteristics.The design and implementation of a novel personalized Web information auto-retrieval system based on small samples is presented.This system adopts a new algorithm of feature extraction and a new method to determine filtering threshold based on small webpage training sets and term-frequency statistics of corpus.Experimental results show that this system can...

Although current search engines based on keywords satisfy some users' need,they can't meet users' personalized demands for their all-purpose characteristics.The design and implementation of a novel personalized Web information auto-retrieval system based on small samples is presented.This system adopts a new algorithm of feature extraction and a new method to determine filtering threshold based on small webpage training sets and term-frequency statistics of corpus.Experimental results show that this system can long-termly and on its own initiative provide more accurate Web information-obtaining service to a user according to his interest than the search engines based on keywords.

基于关键词的搜索引擎满足了人们一定的需要,但由于其通用的性质,并不能满足用户的个性化需求,为此,设计并实现了一个基于示例的个性化Web信息自动获取系统.该系统采用了一种新的基于少量Web示例网页和语料库词频统计的特征抽取算法和过滤阈值设定方法.实验结果表明,较基于关键词的搜索引擎而言,该系统能充分考虑用户的兴趣偏好(示例),长期、主动地向用户提供更加准确的Web信息获取服务.

 
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