Folksonomy-Based Collaborative Tagging System for Classifying Visualized Information in Design Practice 1st Edition by Hyun oh Jung, Min shik Son, Kun pyo Lee – Ebook PDF Instant Download/Delivery. 9783540733454
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ISBN 13: 9783540733454
Author: Hyun oh Jung, Min shik Son, Kun pyo Lee
The aim of this research is to suggest folksonomy-based collaborative tagging system for supporting designers in group who interpret visualized information such as images through grouping, labeling and classifying for design inspiration. We performed field observation and preliminary studies to examine how designers interpret visualized information in group work. We found that traditional classification methods have some problems like lack of surface and time consuming. Based on this research, we developed PC based group work application, named I-VIDI. By implementing I-VIDI based on functional requirements, we have showed how I-VIDI reduces problems found from current image classification methods such as KJ clustering and MDS. In future case study, we plan to conduct extensive user research to evaluate the system further as well as adding more functions which can be usefully applied to collaborative design work.
Folksonomy-Based Collaborative Tagging System for Classifying Visualized Information in Design Practice 1st Table of contents:
- Folksonomy and Collaborative Tagging Systems
- Visualized Information in Design Practice
- System Design and Architecture
- Tagging and Classification Algorithms
- Case Studies and Applications in Design
- Evaluation of the Tagging System
- Challenges and Limitations
- Future Research Directions
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