基于超边相似性的超图聚类改进算法
기우초변상사성적초도취류개진산법
The Improved Algorithm of Hypergraph Clustering based on Hyper Similarity
  • 万方数据
    科技创新与生产力 과기창신여생산력
    Taiyuan Science and Technology
    2015年 10期 113-114 ,共2页

    霍娜%温娟娟%李青云

    곽나%온연연%리청운

    聚类%超图%超边距离阈值 聚類%超圖%超邊距離閾值
    취류%초도%초변거리역치
    clustering%hypergraph%super-edge distance threshold
    在原有超图聚类算法的基础上提出一种基于超边相似性的改进的超图聚类算法, 根据超边距离阈值形成超图模型并采用超图分割法对数据对象进行聚类, 采用簇内奇异特征值进行评估聚类质量.
    재원유초도취류산법적기출상제출일충기우초변상사성적개진적초도취류산법, 근거초변거리역치형성초도모형병채용초도분할법대수거대상진행취류, 채용족내기이특정치진행평고취류질량.
    This paper proposes a improved algorithm of hypergraph clustering based on attribute similarity, on the basis of the original algorithm of hypergraph clustering. According to the threshold-edge distance form the hypergraph model and the hypergraph partitioning method to cluster the data object, using cluster-heads singular eigenvalue to evaluate the quality of clustering.
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