An Interactive Visualization for LDA-based Topic Analysis
Yi Yang; Jian Wang; Guigang Zhang; Weixing Huang
Conference NameThe Second IEEE International Conference on Multimedia Big Data(IEEE BigMM 2016)
Conference Date20-22 April 2016
Conference PlaceCarleton University Ottawa, ON, Canada

LDA-based topic analysis is widely used in text mining field. Considering the large scale of web documents, document clusters are usually analyzed instead of single ones. However, the existing visualizations of LDA-based clustering do not intuitively present contents of hot topics while maintaining the relationships between the topics and the document clusters. In this paper, we propose an integrated interactive visualization method that provides intuitive and effective views for topic popularity, topic contents, document clusters, and relationships between topics and document clusters. In this way, users can quickly identify the topic-based patterns. We show an experimental evaluation by comparing the tabular representation and our visualization. The results show that our method can significantly facilitate the topic analysis, particularly in the field of Chinese culture study.

Document Type会议论文
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Yi Yang,Jian Wang,Guigang Zhang,et al. An Interactive Visualization for LDA-based Topic Analysis[C],2016.
Files in This Item: Download All
File Name/Size DocType Version Access License
07544992.pdf(439KB)会议论文 开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Yi Yang]'s Articles
[Jian Wang]'s Articles
[Guigang Zhang]'s Articles
Baidu academic
Similar articles in Baidu academic
[Yi Yang]'s Articles
[Jian Wang]'s Articles
[Guigang Zhang]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Yi Yang]'s Articles
[Jian Wang]'s Articles
[Guigang Zhang]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 07544992.pdf
Format: Adobe PDF
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.