文章基本信息

标题：Qstack: Multi-tag Visual Rankings
本地全文：下载
作者：Phi Giang Pham ; Mao Lin Huang
期刊名称：Journal of Software
印刷版ISSN：1796-217X
出版年度：2016
卷号：11
期号：7
页码：695-703
DOI：10.17706/jsw.11.7.695-703
出版社：Academy Publisher
摘要：Multi-tag-based search is quite popular on collaborative websites and sharing-online-content systems. For this kind of search results, the challenge is how to compare grouped-tag values of tag collections on heterogeneous alternatives. This paper introduces a new visualization approach named Qstack for dealing with the challenge. Qstack purpose is to help users to visually rank multi-tags based on grouped-score combination within and across the categorized alternatives. The methodology applying interactive stacked bars, dynamic queries and adaptive focus context techniques enables users to easily create and adjust grouped-tag rankings of a large number of heterogeneous alternatives. A case study on Flickr photo award allocation will be presented for Qstack demonstration. We conducted a qualitative study for evaluating Qstack effectiveness, and the result indicates that our approach is useful for multi-tag rankings.
其他关键词：Multiple tags, visual rankings, interactive stacked bars.