科技通报
科技通報
과기통보
BULLETIN OF SCIENCE AND TECHNOLOGY
2014年
2期
96-98,101
,共4页
日志聚类%社区挖掘%网络社区%动态中心
日誌聚類%社區挖掘%網絡社區%動態中心
일지취류%사구알굴%망락사구%동태중심
log clustering%community mining%online communities%dynamic center
针对现有的网络社区挖掘算法在社区划分的质量不高及执行效率低的问题,提出了一种基于日志聚类的邮件网络社区挖掘算法LENCM(the log clustering based e-mail network community mining al-gorithm),算法根据日志聚类节点的密度变化确定核心节点,构成日志连通子图并确定邮件网络社区划分的初始社区中心点和个数,采用错误注入的方式构造算子,并把执行后的日志与关联规则进行比较,借助社区中心动态调整方法将非核心节点划分至所属社区。实验证明基于日志聚类的邮件网络社区划分挖掘算法有较高的划分质量和较快的执行效率,具有一定的有效性和可行性。
針對現有的網絡社區挖掘算法在社區劃分的質量不高及執行效率低的問題,提齣瞭一種基于日誌聚類的郵件網絡社區挖掘算法LENCM(the log clustering based e-mail network community mining al-gorithm),算法根據日誌聚類節點的密度變化確定覈心節點,構成日誌連通子圖併確定郵件網絡社區劃分的初始社區中心點和箇數,採用錯誤註入的方式構造算子,併把執行後的日誌與關聯規則進行比較,藉助社區中心動態調整方法將非覈心節點劃分至所屬社區。實驗證明基于日誌聚類的郵件網絡社區劃分挖掘算法有較高的劃分質量和較快的執行效率,具有一定的有效性和可行性。
침대현유적망락사구알굴산법재사구화분적질량불고급집행효솔저적문제,제출료일충기우일지취류적유건망락사구알굴산법LENCM(the log clustering based e-mail network community mining al-gorithm),산법근거일지취류절점적밀도변화학정핵심절점,구성일지련통자도병학정유건망락사구화분적초시사구중심점화개수,채용착오주입적방식구조산자,병파집행후적일지여관련규칙진행비교,차조사구중심동태조정방법장비핵심절점화분지소속사구。실험증명기우일지취류적유건망락사구화분알굴산법유교고적화분질량화교쾌적집행효솔,구유일정적유효성화가행성。
Research the quality and efficiency of network community partition. The paper puts forward A mail network community partition mining algorithm based on log clustering. The algorithm determines the core node by the change of the log cluster node density, constitutes the logs connected subgraph, determines the initial community center point and the number of e-mail network community, adopts the way of error injection to construct operator, and makes the imple-mentation of the log compared with association rules with the community center dynamically adjust the division of the non-core nodes to their respective communities. The experimental results show that the improved algorithm has higher divided quality and faster execution efficiency.