Searches based on content similarities in large multimedia libraries are essentially K nearest neighbor searches in high dimensional spaces.

Several major flow pattern identification methods are introduced: nearest neighbor method, K nearest neighbor, neural network and feature extraction method.

介绍了流型辨识的几种主要的方法：最近邻法、K近邻算法、神经网络法和特征提取法。

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Therefore, moving object index strategy and K nearest neighbor query strategy need to be studied.

因此需要研究基于路网的移动对象索引策略和K近邻查询策略，如何采用快速、有效的方法来处理移动对象K近邻查询是一个具有挑战性的研究课题。

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Two-tier K Nearest Neighbor Algorithm Based on Active Diagnostic Recommendation

基于主动诊断推荐的双层K-最近邻算法

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Finally, an emotion recognition experiment based on K Nearest Neighbor is described.

最后利用K最近邻方法对汉语情感语料进行识别。

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We also introduce a simple confusing data method: K nearest neighbor algorithm.

并提出将k最近邻分类方法用于分类结果融合；

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Obviously, the experimental result shows that, in multi-level decomposition, the method is better than the traditional Bayes and K-Nearest Neighbor ( KNN) classification in recognition rate.

实验结果显示，该方法在多层小波分解的情况下，对于少数民族文种识别的精度好于传统的贝叶斯和KNN。

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This paper implemented an improved K-Nearest Neighbor ( Fuzzy KNN) algorithm in which Fuzzy Adaptive Resonance Theory ( ART) is applied in K-NN classification to make a new algorithm.

提出了一种K-最近邻改进算法，该算法用模糊自适应共振理论（Fuzzy ART）对K-最近邻的训练样本集进行浓缩，以改善K-最近邻的计算速度。

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The kernel based weighted KNN algorithm solves the multi peak distribution problem and the overlap boundary problem of the sample set, as well as the classifier's precise decision problem.

基于核的距离加权KNN算法解决了样本的多峰分布、边界重叠问题和分类器的精确分类决策问题。

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To improve the design of classifier and training time, a new method combining the clonal selection algorithm and K nearest neighbor ( CSA+ KNN) is proposed.

针对植物叶片识别中分类器设计和训练识别时间较长的问题，提出了一种基于克隆选择算法和K近邻判别分析（CSA+KNN）的叶片识别方法。

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This paper introduces the flow of Chinese text classification and relevant technologies, and an improved KNN method is proposed on the basis of analyzing the disadvantage of traditional KNN method.

介绍了基于KNN方法的中文文本分类流程及相关技术，在分析传统KNN方法不足的基础上提出一种改进的KNN方法。

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The emphasis of this paper is a method based on the contents& KNN. A furthermore experiment tests the effects of the categorization techniques of Chinese Web texts.

最后通过实验测试了使用KNN算法的中文Web文本分类技术的效果。

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This paper introduces an effect query algorithm based on TPR tree, such algorithm can support kNN query for moving objects and has a better performance than known algorithms.

该文在TPR树这一时空索引的基础上，提出了一种高效的最近邻查询算法，能够支持移动对象的多个最近邻对象的查询，并在性能上也有所提高。

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A new method for fault diagnosis of large-scale analogue circuits with tolerance based on body algorithm and Kohonen neural networks ( KNN) is presented in the paper.

提出了一种基于集团法和自组织神经网络的容差电路故障诊断方法。

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Experimental results show that B-KNN method remarkably outperforms KNN method, and it is more suitable for classification tasks with deep hierarchy categorization space.

实验结果表明，与KNN相比，B-KNN的性能有较大提升，更适用于具有较深层次类型空间的文本分类应用。

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The KNN Media Center is a new landmark broadcast headquarters and cultural media facility located in Busan's Centum City.

在最近邻媒体中心是一个新的里程碑广播总部和文化传媒设施，釜山的多功能城市位置。

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Feature weighting is one of the important problems for feature weighting based KNN algorithm, and many heuristic methods have been employed to solve the problem traditionally.

特征权重学习是基于特征赋权的K近邻算法需要解决的重要问题之一，传统上提出了许多启发式的学习方法。

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The main point of this program is based on pattern recognition techniques, the chief structure feature of an unknown can be obtained from the KNN classification results.

本程序主要是以模式识别技术为基础，实现了对未知物谱图的KNN分类，进而得到未知物的主要结构特征。

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Improved KNN algorithm by using the combination technology, and applied it to the forecast of non-mining fracture of shaft-lining of mine.

利用组合技术对KNN算法进行改进，并将其应用于煤矿立井井筒非采动破裂的预测。

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One search Model is based on BP neural network and another based on K-Nearest-Neighbor ( KNN) algorithm, a dynamic weight tuning algorithm is proposed.

基于BP神经网络的检索模型和基于最近邻居法的检索模型，并给出了一种权重动态调节方法；

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Especially, it discusses some key techniques such as web page classification model, purity of web page, weight of feature, KNN classification.

描述了一个完整的中文网页分类系统的设计和实现过程，重点介绍了网页分类中的网页净化、特征加权、KNN分类等关键技术。

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