基于上下文语义图的专题文档集子主题可视化

2015 International Conference on Computational Science and Computational Intelligence (CSCI) Pub Date : 2015-12-07 DOI:10.1109/CSCI.2015.124

A. Sboev, I. Moloshnikov, D. Gudovskikh, R. Rybka

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引用次数: 0

摘要

提出了一种在大型文档集合中实现嵌套主题可视化的方法。该方法基于一组参数:信息熵、Kullback-Leibler散度、Ginzburg算法、文档中关键字和关键短语的分布与伯努利理论分布的相似性。将我们的方法与基于TF-IDF方法的实现进行了比较。

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Visualization of Subtopics of the Thematic Document Collection Using the Context-Semantic Graph

An approach for visualization of nested topics within large collections of documents is proposed. The approach is based on set of parameters: information entropy, Kullback-Leibler divergence, Ginzburg algorithm, similarity the distributions of keywords and key phrases in the documents with Bernoulli's theoretical distributions. The results of comparisons of our approach with implementations based on TF-IDF approaches are presented.

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2015 International Conference on Computational Science and Computational Intelligence (CSCI)

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