HOT TOPIC DETECTION ALGORITHM BASED ON IMPROVED K-MEANS ALGORITHM

摘要：

　　Discovery algorithm based on improved K-means clustering algorithm Internet hotspots.Algorithm by mutations of the smallest maximum distance in the text vector,the K value and the choice of the initial accumulation point,according to the judgment of the validity of the final clustering results to obtain the best clustering results and end the hot Internet information.The improved algorithm overcomes the choice of the classic K-means algorithm,K value and the volatility of the shortcomings of clustering results can be effectively applied to the hot spots found in the function of the network information.The final experimental results show that the proposed algorithm is correct and effective.

关键词： Network public opinion Hot topic discovery Text clustering K-means algorithm

作者: Xunxun Chen Wei Wang Dapeng Man Shichang Xuan

作者单位: National Computer Network Emergency Response Technical Team Coordination Center,Beijing 100029,China School of Computer Science and Technology,Harbin Engineering University,Harbin 150001 China

会议类型: 国际会议

会议名称: 2012 2nd IEEE International Conference on Cloud Computing and Intelligence Systems (2012年第2届IEEE云计算与智能系统国际会议(IEEE CCIS2012))

会议地点: 杭州

会议语种:英文

页码: 814-817

在线出版日期: 2012-10-30（万方平台首次上网日期，不代表论文的发表时间）