NDLI: A visualization system for web retrieved credit information

Content Provider	IEEE Xplore Digital Library
Author	Lirong Xiong Mengjun Wang Jing Fan
Copyright Year	2011
Description	Author affiliation: College of Computer Science and Technology, Zhejiang University, Hangzhou, China (Lirong Xiong) \|\| College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China (Mengjun Wang; Jing Fan)
Abstract	Information retrieved with traditional method results in linear lists which lack of effective filtration, organization, and aggregation. How to organize and visualize the retrieved information result set effectively and how to provide users with the effective interaction becomes increasingly important. Based on the Information Visualization Model, this paper studies the key technologies. The data clustering methods and suitable display technologies are analyzed. Then, this paper proposes an information visualization model for credit domain, and describes a visualization system for web retrieved credit information. The system can crawl credit related web pages, and after analyzing the characteristics of credit information, SOM-based clustering method is applied to well organize the web pages, and visualization technology is used to present the documents information globally and locally. In this way, user can understand credit information better. At last, examples of visual display for credit information are shown in this paper.
Starting Page	728
Ending Page	733
File Size	695506
Page Count	6
File Format	PDF
ISBN	9781424499502
ISSN	21579563
e-ISBN	9781424499533
DOI	10.1109/ICNC.2011.6022206
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	SOM Visualization self-organization map Clustering methods Data visualization Clustering algorithms Web pages information visualization Data mining credit visualization system
Content Type	Text
Resource Type	Article

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