Generation of conceptual-level text cloud with graph diffusion

Ying Chun Lin, Po An Yang, Yen Kuan Lee, Kun Ta Chuang

研究成果: Conference contribution

摘要

In this paper, we explore a novel framework to generate a well-known text cloud visualization with the conceptual sense. The traditional text cloud is usually generated according to the word occurrence, possibly including the idf-based concept for word weight. The solution is applicable for the long articles. However, for a set of short sentences such as daily news titles, we cannot easily understand the weight of each keyword and its importance to users since the idf value and occurrence in short sentences are difficult to be both well discriminative. In this paper, we propose a graph-based diffusion model to generate conceptual level keyword cloud. We utilize the RDF-based Wikipedia word relation and apply in the Chinese news titles from different news sources. The result shows that our visualization can easily capture the importance concept revealed in a set of news titles.

原文English
主出版物標題Proceedings of the 28th Conference on Computational Linguistics and Speech Processing, ROCLING 2016
編輯Chung-Hsien Wu, Yuen-Hsien Tseng, Hung-Yu Kao, Lun-Wei Ku, Yu Tsao, Shih-Hung Wu
發行者The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
頁面402-411
頁數10
ISBN(電子)9789573079293
出版狀態Published - 2016 十月 1
事件28th Conference on Computational Linguistics and Speech Processing, ROCLING 2016 - Tainan, Taiwan
持續時間: 2016 十月 62016 十月 7

出版系列

名字Proceedings of the 28th Conference on Computational Linguistics and Speech Processing, ROCLING 2016

Conference

Conference28th Conference on Computational Linguistics and Speech Processing, ROCLING 2016
國家Taiwan
城市Tainan
期間16-10-0616-10-07

All Science Journal Classification (ASJC) codes

  • Speech and Hearing
  • Language and Linguistics

指紋 深入研究「Generation of conceptual-level text cloud with graph diffusion」主題。共同形成了獨特的指紋。

引用此