主题检测与跟踪任务中主题与聚类的构建

M. Mohd, F. Crestani, I. Ruthven
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引用次数: 5

摘要

本文讨论了主题检测与跟踪任务中待跟踪主题和待检测聚类的构造。采用单次聚类方法对新闻文章进行聚类。因此,TDT任务包含了基于f1度量的良好和较差的聚类性能的组合。因此,从聚类实验中选择聚类和主题在跟踪和检测任务中非常重要。它为用户实验设计做出了贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Construction of topics and clusters in Topic Detection and Tracking tasks
This paper discussed the construction of topics to be tracked and clusters to be detected in Topic Detection and Tracking (TDT) tasks. Single Pass Clustering was used to cluster the news articles. As a result, the TDT tasks contained a combination of a good and poor clustering performance based on the F1-measure. Therefore, the selection of clusters and topics from the clustering experiment is important in the Tracking and the Detection tasks. It has contributed towards the user experimental design.
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