CorrelatedMultiples: Spatially Coherent Small Multiples With Constrained Multi‐Dimensional Scaling

Liu Xiaotong; Hu Yifan; North Stephen; Shen Han‐Wei

摘要

Abstract > Displaying small multiples is a popular method for visually summarizing and comparing multiple facets of a complex data set. If the correlations between the data are not considered when displaying the multiples, searching and comparing specific items become more difficult since a sequential scan of the display is often required. To address this issue, we introduce CorrelatedMultiples, a spatially coherent visualization based on small multiples, where the items are placed so that the distances reflect their dissimilarities. We propose a constrained multi‐dimensional scaling (CMDS) solver that preserves spatial proximity while forcing the items to remain within a fixed region. We evaluate the effectiveness of our approach by comparing CMDS with other competing methods through a controlled user study and a quantitative study, and demonstrate the usefulness of CorrelatedMultiples for visual search and comparison in three real‐world case studies . </abstract> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> <div class="translation abstracttxt"> <span class="zhankaihshouqi fivelineshidden" id="abstract"> <span>机译：</span><Abstract Type =“Main”XML：Lang =“en”> <标题类型=“main”>抽象</ title> > 显示小倍数是一种流行的方法，用于视觉上总结和比较多个方面的多个方面复杂数据集。如果在显示倍数时不考虑数据之间的相关性，则搜索和比较特定项变得更加困难，因为通常需要显示显示的顺序扫描。为了解决这个问题，我们引入相关性，基于小倍的空间相干的可视化，其中物品被放置，使得距离反映出它们的异化。我们提出了一个受约束的多维缩放（CMDS）求解器，其保留空间接近度，同时强迫物品保留在固定区域内。通过对照用户学习和定量研究，我们通过将CMDS与其他竞争方法进行比较来评估我们的方法的有效性，并证明了在三个真实案例研究中对视觉搜索和比较的相关性的有用性</ i>。 </ p> </ abstract> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> </div> <div class="record"> <h2 class="all_title" id="enpatent33" > 著录项</h2> <ul> <li> <span class="lefttit">来源</span> <div style="width: 86%;vertical-align: text-top;display: inline-block;"> <a href='/journal-foreign-16902/'>《Computer Graphics Forum: Journal of the European Association for Computer Graphics 》</a> <b style="margin: 0 2px;">|</b><span>2018年第1期</span><b style="margin: 0 2px;">|</b> <span>共12页</span> </div> </li> <li> <div class="author"> <span class="lefttit">作者</span> <p id="fAuthorthree" class="threelineshidden zhankaihshouqi"> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Liu Xiaotong&option=202" target="_blank" rel="nofollow">Liu Xiaotong;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Hu Yifan&option=202" target="_blank" rel="nofollow">Hu Yifan;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=North Stephen&option=202" target="_blank" rel="nofollow">North Stephen;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Shen Han‐Wei&option=202" target="_blank" rel="nofollow">Shen Han‐Wei;</a> </p> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zkzz" style="display: none;">展开▼</span> </div> </li> <li> <div style="display: flex;"> <span class="lefttit">作者单位</span> <div style="position: relative;margin-left: 3px;max-width: 639px;"> <div class="threelineshidden zhankaihshouqi" id="fOrgthree"> <p>Department of Computer Science and EngineeringThe Ohio State UniversityColumbus OH USA;</p> <p>Yahoo LabsNew York NY USA;</p> <p>InfovisibleLLCOldwick NJ USA;</p> <p>Department of Computer Science and EngineeringThe Ohio State UniversityColumbus OH USA;</p> </div> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zhdw" style="display: none;">展开▼</span> </div> </div> </li> <li> <span class="lefttit">收录信息</span> <span style="width: 86%;vertical-align: text-top;display: inline-block;"></span> </li> <li> <span class="lefttit">原文格式</span> <span>PDF</span> </li> <li> <span class="lefttit">正文语种</span> <span>eng</span> </li> <li> <span class="lefttit">中图分类</span> <span> <a href="https://www.zhangqiaokeyan.com/clc/7754.html" title="计算机的应用">计算机的应用 ;</a></span> </li> <li class="antistop"> <span class="lefttit">关键词</span> <p style="width: 86%;vertical-align: text-top;"> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=information visualization&option=203" rel="nofollow">information visualization;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=small multiples&option=203" rel="nofollow">small multiples;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=multi‐dimensional scaling&option=203" rel="nofollow">multi‐dimensional scaling;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=I.3.3 Computer Graphics: Picture/Image Generation‐Display algorithms&option=203" rel="nofollow">I.3.3 Computer Graphics: Picture/Image Generation‐Display algorithms;</a> </p> <div class="translation"> 机译：信息可视化;小倍数;多维缩放;I.3.3 [计算机图形]：图片/图像生成 - 显示算法; </div> </li> </ul> </div> </div> <div class="literature cardcommon"> <div class="similarity "> <h3 class="all_title" id="enpatent66">相似文献</h3> <div class="similaritytab clearfix"> <ul> <li class="active" >外文文献</li> <li >中文文献</li> <li >专利</li> </ul> </div> <div class="similarity_details"> <ul > <li> <div> <b>1. </b><a class="enjiyixqcontent" href="/journal-foreign-detail/0704022260258.html">CorrelatedMultiples: Spatially Coherent Small Multiples With Constrained Multi‐Dimensional Scaling</a> <b>[J]</b> . <span> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Liu Xiaotong&option=202" target="_blank" rel="nofollow" class="tuijian_auth tuijian_authcolor">Liu Xiaotong,</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Hu Yifan&option=202" target="_blank" rel="nofollow" class="tuijian_auth tuijian_authcolor">Hu Yifan,</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=North 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