کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6857118 | 661905 | 2016 | 45 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A task-based evaluation of combined set and network visualization
ترجمه فارسی عنوان
ارزیابی مبتنی بر وظیفه مجموعه و تجسم شبکه
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کلمات کلیدی
تنظیم تجسم، تجسم گراف، تجسم ترکیبی، خوشه بندی شبکه های،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
This paper addresses the problem of how best to visualize network data grouped into overlapping sets. We address it by evaluating various existing techniques alongside a new technique. Such data arise in many areas, including social network analysis, gene expression data, and crime analysis. We begin by investigating the strengths and weakness of four existing techniques, namely Bubble Sets, EulerView, KelpFusion, and LineSets, using principles from psychology and known layout guides. Using insights gained, we propose a new technique, SetNet, that may overcome limitations of earlier methods. We conducted a comparative crowdsourced user study to evaluate all five techniques based on tasks that require information from both the network and the sets. We established that EulerView and SetNet, both of which draw the sets first, yield significantly faster user responses than Bubble Sets, KelpFusion and LineSets, all of which draw the network first.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volumes 367â368, 1 November 2016, Pages 58-79
Journal: Information Sciences - Volumes 367â368, 1 November 2016, Pages 58-79
نویسندگان
Peter Rodgers, Gem Stapleton, Bilal Alsallakh, Luana Michallef, Rob Baker, Simon Thompson,