Bag of Timestamps: A Simple and Efficient Bayesian Chronological Mining

机译：时间戳记包：一种简单高效的贝叶斯年表挖掘

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In this paper, we propose a new probabilistic model, Bag of Timestamps (BoT), for chronological text mining. BoT is an extension of latent Dirichlet allocation (LDA), and has two remarkable features when compared with a previously proposed Topics over Time (ToT), which is also an extension of LDA. First, we can avoid overfitting to temporal data, because temporal data are modeled in a Bayesian manner similar to word frequencies. Second, BoT has a conditional probability where no functions requiring time-consuming computations appear. The experiments using newswire documents show that BoT achieves more moderate fitting to temporal data in shorter execution time than ToT.

机译：在本文中，我们提出了一种用于按时间顺序进行文本挖掘的新概率模型，即“时间戳记袋”（BoT）。 BoT是潜在Dirichlet分配（LDA）的扩展，并且与先前提出的随时间变化的主题（ToT）相比，它具有两个显着特征，后者也是LDA的扩展。首先，我们可以避免过度拟合时态数据，因为时态数据是以类似于词频的贝叶斯方式建模的。其次，BoT具有条件概率，其中没有需要耗时计算的函数出现。使用新闻专线文档进行的实验表明，与ToT相比，BoT在更短的执行时间内可以更适度地适应时间数据。

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来源
《Advances in data and web management》|2009年|556-561|共6页
会议地点 Suzhou(CN)
作者
Tomonari Masada; Atsuhiro Takasu; Tsuyoshi Hamada; Yuichiro Shibata; Kiyoshi Oguri;
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作者单位

Nagasaki University, 1-14 Bunkyo-machi, Nagasaki, Japan;

National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, Japan;

Nagasaki University, 1-14 Bunkyo-machi, Nagasaki, Japan;

Nagasaki University, 1-14 Bunkyo-machi, Nagasaki, Japan;

Nagasaki University, 1-14 Bunkyo-machi, Nagasaki, Japan;

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正文语种 eng
中图分类计算机网络;
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机译：时间戳袋：简单高效的贝叶斯时间序列挖掘

Bag of Timestamps: A Simple and Efficient Bayesian Chronological Mining

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