Worbel: Aggregating Point Labels into Word Clouds

Sujoy Bhore, Robert Ganian, Guangping Li, Martin Nöllenburg, Jules Wulms

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Point feature labeling is a classical problem in cartography and GIS that has been extensively studied for geospatial point data. At the same time, word clouds are a popular visualization tool to show the most important words in text data which has also been extended to visualize geospatial data (Buchin et al. PacificVis 2016). In this paper, we study a hybrid visualization, which combines aspects of word clouds and point labeling. In the considered setting, the input data consists of a set of points grouped into categories and our aim is to place multiple disjoint and axis-aligned rectangles, each representing a category, such that they cover points of (mostly) the same category under some natural quality constraints. In our visualization, we then place category names inside the computed rectangles to produce a labeling of the covered points which summarizes the predominant categories globally (in a word-cloud-like fashion) while locally avoiding excessive misrepresentation of points (i.e., retaining the precision of point labeling). We show that computing a minimum set of such rectangles is NP-hard. Hence, we turn our attention to developing heuristics and exact SAT models to compute our visualizations. We evaluate our algorithms quantitatively, measuring running time and quality of the produced solutions, on several artificial and real-world data sets. Our experiments show that the heuristics produce solutions of comparable quality to the SAT models while running much faster.

Original languageEnglish
Title of host publication29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021
EditorsXiaofeng Meng, Fusheng Wang, Chang-Tien Lu, Yan Huang, Shashi Shekhar, Xing Xie
PublisherAssociation for Computing Machinery
Pages256-267
Number of pages12
ISBN (Electronic)9781450386647
DOIs
StatePublished - 2 Nov 2021
Externally publishedYes
Event29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021 - Virtual, Online, China
Duration: 2 Nov 20215 Nov 2021

Publication series

NameGIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

Conference

Conference29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021
Country/TerritoryChina
CityVirtual, Online
Period2/11/215/11/21

Keywords

  • categorical point data
  • labeling
  • word clouds

ASJC Scopus subject areas

  • Earth-Surface Processes
  • Computer Science Applications
  • Modeling and Simulation
  • Computer Graphics and Computer-Aided Design
  • Information Systems

Fingerprint

Dive into the research topics of 'Worbel: Aggregating Point Labels into Word Clouds'. Together they form a unique fingerprint.

Cite this