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072282
- 提出了一种自动构造特定领域本体的方法，该方法应用术语抽取和多重聚类技术。在术语抽取阶段，通过术语在专业语料与背景语料中出现概率的对比，采用LLR公式对术语进行评分，取得了更好的抽取效果。在层级关系发现过程中，采用上下文共现信息结合HowNet中词语的语义相似度，进行术语间相似度度量，力求获得术语间最合理的相关状况。同时改进了k-medoids聚类算法，更准确地发现术语的层级关系，进而构造出特定领域的本体。-This paper pres
83390086medoids
- its all about implimentation of k mediods
k-medoids
- k-medoids实现网络社区聚类，含有使用说明书和算法原理-k-medoids clustering for network communities, containing instructions and algorithm theory
kmedioids
- [inds,cidx] = kmedioids(D,k) Performs k-mediods clustering only requires a distance matrix D and number of clusters k. Finds cluster assignments "inds" to minimize the following cost function: -[inds,cidx] =
k-mediods
- 用于图像特征的K中心点聚类(k-mediods)的matlab实现。-k-mediods implements by matlab, used for cluster of image feature
83390086medoids
- its all about implimentation of k mediods
Kmeans_medoids
- k-means和k-mediods的JAVA实现。直接读取文档数据，适用于二维数据。-k-means and k-Medoids clustering algorithm JAVA implementation. Document data read directly,suitable for two-dimensional data.
Kmediods
- 利用java语言，对K-mediods算法的实现和应用(Implementation and application of K-mediods algorithm)