Please wait a minute...
Data Analysis and Knowledge Discovery
Current Issue | Archive | Adv Search |
Research on the Visualization Method of Drawing Technology Theme Map with Clusters
Wang Xuefeng,Ren Huichao,Liu Yuqin
(School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China) (School of Journalism and Publishing, Beijing Institute of Graphic Communication, Beijing 102600, China)
Download:
Export: BibTeX | EndNote (RIS)      
Abstract  

[Purpose]In order to make up for the limited recognizability of the single color technology topic map after clustering, enhance the expressiveness of the technology topic map and enrich the drawing methods of technology topic map and the selection range of software tools for  analysts.[Method]A visualization method of technology topic map with clusters is proposed. The layout algorithm is applied to layout the topic words, and the pixel density function, class density function and color intensity function are established. According to the class density and color intensity value, the color rendering is carried out, and the clustering technology topic map is obtained. [Results] The method is embedded in itginsight software,which is a text mining and visualization software tool, and applied to the case analysis of quantum cryptography communication patent data, the results show that the method is simple and effective.

Key words Technical Distribution      Theme Map      Visualization      Clustering      
Published: 20 October 2021
ZTFLH:  TP391  

Cite this article:

Wang Xuefeng, Ren Huichao, Liu Yuqin. Research on the Visualization Method of Drawing Technology Theme Map with Clusters . Data Analysis and Knowledge Discovery, 0, (): 1-.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467. 2021.0858     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y0/V/I/1

[1] Wang Ruolin, Niu Zhendong, Lin Qika, Zhu Yifan, Qiu Ping, Lu Hao, Liu Donglei. Disambiguating Author Names with Embedding Heterogeneous Information and Attentive RNN Clustering Parameters[J]. 数据分析与知识发现, 2021, 5(8): 13-24.
[2] Wang Xiwei,Jia Ruonan,Wei Yanan,Zhang Liu. Clustering User Groups of Public Opinion Events from Multi-dimensional Social Network[J]. 数据分析与知识发现, 2021, 5(6): 25-35.
[3] Lu Linong,Zhu Zhongming,Zhang Wangqiang,Wang Xiaochun. Cross-database Knowledge Integration and Fingerprint of Institutional Repositories with Lingo3G Clustering Algorithm[J]. 数据分析与知识发现, 2021, 5(5): 127-132.
[4] Zhang Mengyao, Zhu Guangli, Zhang Shunxiang, Zhang Biao. Grouping Microblog Users of Trending Topics Based on Sentiment Analysis[J]. 数据分析与知识发现, 2021, 5(2): 43-49.
[5] Ding Hao, Ai Wenhua, Hu Guangwei, Li Shuqing, Suo Wei. A Personalized Recommendation Model with Time Series Fluctuation of User Interest[J]. 数据分析与知识发现, 2021, 5(11): 45-58.
[6] Yang Chen, Chen Xiaohong, Wang Chuhan, Liu Tingting. Recommendation Strategy Based on Users’ Preferences for Fine-Grained Attributes[J]. 数据分析与知识发现, 2021, 5(10): 94-102.
[7] Yu Fengchang,Cheng Qikai,Lu Wei. Locating Academic Literature Figures and Tables with Geometric Object Clustering[J]. 数据分析与知识发现, 2021, 5(1): 140-149.
[8] Wu Jinming,Hou Yuefang,Cui Lei. Automatic Expression of Co-occurrence Clustering Based on Indexing Rules of Medical Subject Headings[J]. 数据分析与知识发现, 2020, 4(9): 133-144.
[9] Wen Pingmei,Ye Zhiwei,Ding Wenjian,Liu Ying,Xu Jian. Developments of Named Entity Disambiguation[J]. 数据分析与知识发现, 2020, 4(9): 15-25.
[10] Xi Yunjiang, Du Diedie, Liao Xiao, Zhang Xuehong. Analyzing & Clustering Enterprise Microblog Users with Supernetwork[J]. 数据分析与知识发现, 2020, 4(8): 107-118.
[11] Yang Xu,Qian Xiaodong. Synchronous Clustering Algorithm for Social Networks Based on Improved Vicsek Model[J]. 数据分析与知识发现, 2020, 4(4): 119-128.
[12] Xiong Huixiang,Li Xiaomin,Li Yueyan. Group Recommendation Based on Attribute Mining of Book Reviews[J]. 数据分析与知识发现, 2020, 4(2/3): 214-222.
[13] Chen Ting,Wang Haiming,Wang Xiaomei. Detecting Funding Topics Evolutions with Visualization[J]. 数据分析与知识发现, 2020, 4(2/3): 60-67.
[14] Wang Xiwei,Zhang Liu,Huang Bo,Wei Ya’nan. Constructing Topic Graph for Weibo Users Based on LDA: Case Study of “Egypt Air Disaster”[J]. 数据分析与知识发现, 2020, 4(10): 47-57.
[15] Wei Jiaze,Dong Cheng,He Yanqing,Liu Zhihui,Peng Keyun. Detecting News Topics Based on Equalized Paragraph and Sub-topic Vector[J]. 数据分析与知识发现, 2020, 4(10): 70-79.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn