Topic Structure Modeling

机译：主题结构建模

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摘要

In this paper, we present a method based on document probes to quantify and diagnose topic structure, distinguishing topics as monolithic, structured, or diffuse. The method also yields a structure analysis that can be used directly to optimize filter (classifier) creation. Preliminary results illustrate the predictive value of the approach on TREC/R.euters-96 topics.

机译：在本文中，我们提出了一种基于文档探针的方法来量化和诊断主题结构，将主题区分为单片，结构化或漫射。该方法还产生了一种结构分析，可以直接用于优化滤波器（分类器）创建。初步结果说明了TREC / R.EUTERS-96主题的方法的预测值。

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《Annual international ACM SIGIR conference on research and development in information retrieval》|2002年||共2页
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David A. Evans; James G. Shanahan; Victor Sheftel;
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正文语种
中图分类情报检索;
关键词
topic structure; topic modeling; clustering; probes;

机译：主题结构;主题建模;聚类;探针;

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专利

1. Structured Neural Topic Models for Reviews [J] . Babak Esmaeili, Hongyi Huang, Byron Wallace, JMLR: Workshop and Conference Proceedings . 2018,第2010期

机译：结构化神经主题模型的评论
2. Structured Neural Topic Models for Reviews [J] . Babak Esmaeili, Hongyi Huang, Byron Wallace, JMLR: Workshop and Conference Proceedings . 2018,第2009期

机译：结构化神经主题模型的评论
3. When Are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity [J] . Animashree Anandkumar, Daniel Hsu, Majid Janzamin, Journal of machine learning research . 2015,第Apr期

机译：什么时候可以识别出不完整的主题模型？具有结构稀疏性的Tensor Tucker分解的唯一性
4. Topic Segmentation with a Structured Topic Model [C] . Lan Du, Wray Buntine, Mark Johnson Conference of the North American Chapter of the Association for Computational Linguistics: human language technologies . 2013

机译：结构化主题模型的主题细分
5. Structured topic models: Jointly modeling words and their accompanying modalities. [D] . Wang, Xuerui. 2009

机译：结构化主题模型：联合建模单词及其伴随的方式。
6. Structured Correspondence Topic Models for Mining Captioned Figures in Biological Literature [O] . Amr Ahmed, Eric P. Xing, William W. Cohen, -1

机译：生物文献中带字幕人物的结构化对应主题模型
7. Improving Event Coreference Resolution by Modeling Correlations between Event Coreference Chains and Document Topic Structures [O] . Prafulla Kumar Choubey, Ruihong Huang 2018

机译：通过建模事件Coreference链和文档主题结构之间的相关性提高事件培训决策
8. When are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity. [R] . Anandkumar, A., Hsu, D., Janzamin, M., 2013

机译：何时超完整主题模型可识别？具有结构稀疏性的Tensor Tucker分解的唯一性。

Topic Structure Modeling

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