《Table 6 Results on the sports dataset》

  提示：宽带有限、当前游客访问压缩模式

本系列图表出处文件名：随高清版一同展现

《A document-level model for tweet event detection》

1. 获取 高清版本忘记账户？点击这里登录

1. 下载图表忘记账户？点击这里登录

To evaluate the robustness of the method，the results（forth line）are compared with the baseline methods of Ref.[9]on the sports dataset，shown in Table 6.Sensor（third line）shows the proposed method in Ref.[9]，which is discussed in Section 3.The first two lines in Table 6 show results of two strong baseline methods，which are selected from Ref.[9].The LDA method is a topic model based on event detection method，which uses LDA（Latent Dirichlet Allocation）for clustering.Doc-p is a document-based topic detection method by Locality Sensitive Hashing.The method improves the topic recall from 76.92%by Sensor and Doc-p to 88.89%.Keyword precision and recall are also improved compared to all baseline methods.The improvement verifies the effectiveness of our method on the sports domain，which shows the robustness of the method.