8 Search Results for "Telea, Alexandru"

Document
DOI: 10.4230/LIPIcs.GD.2025.22
NNP-NET: Accelerating t-SNE Graph Drawing for Very Large Graphs by Neural Networks

Authors: Ilan Hartskeerl, Tamara Mchedlidze, Simon van Wageningen, Peter Vangorp, and Alexandru Telea

Published in: LIPIcs, Volume 357, 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)

Abstract
tsNET is a recent graph drawing (GD) method that creates high quality layouts but suffers from a very high runtime. We present a new GD method, NNP-NET, which reduces tsNET’s time complexity to generate layouts for very large graphs in seconds. Additionally, we extend tsNET to support drawing graphs with edge weights. We accomplish this by replacing tsNET’s t-SNE projection with Neural Network Projection (NNP), a fast dimensionality reduction (DR) method that can imitate any given DR method. Our experiments show that NNP-NET gets good quality results when compared to other state-of-the art GD methods while yielding a better computational scalability.
Cite as

Ilan Hartskeerl, Tamara Mchedlidze, Simon van Wageningen, Peter Vangorp, and Alexandru Telea. NNP-NET: Accelerating t-SNE Graph Drawing for Very Large Graphs by Neural Networks. In 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 357, pp. 22:1-22:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{hartskeerl_et_al:LIPIcs.GD.2025.22,
  author =	{Hartskeerl, Ilan and Mchedlidze, Tamara and van Wageningen, Simon and Vangorp, Peter and Telea, Alexandru},
  title =	{{NNP-NET: Accelerating t-SNE Graph Drawing for Very Large Graphs by Neural Networks}},
  booktitle =	{33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)},
  pages =	{22:1--22:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-403-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{357},
  editor =	{Dujmovi\'{c}, Vida and Montecchiani, Fabrizio},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GD.2025.22},
  URN =		{urn:nbn:de:0030-drops-250087},
  doi =		{10.4230/LIPIcs.GD.2025.22},
  annote =	{Keywords: supervised graph drawing, dimensionality reduction, t-SNE}
}
Document
DOI: 10.4230/LIPIcs.GD.2025.7
Same Quality Metrics, Different Graph Drawings

Authors: Simon van Wageningen, Tamara Mchedlidze, and Alexandru C. Telea

Published in: LIPIcs, Volume 357, 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)

Abstract
Graph drawings are commonly used to visualize relational data. User understanding and performance are linked to the quality of such drawings, which is measured by quality metrics. The tacit knowledge in the graph drawing community about these quality metrics is that they are not always able to accurately capture the quality of graph drawings. In particular, such metrics may rate drawings with very poor quality as very good. In this work we make this tacit knowledge explicit by showing that we can modify existing graph drawings into arbitrary target shapes while keeping one or more quality metrics almost identical. This supports the claim that more advanced quality metrics are needed to capture the "goodness" of a graph drawing and that we cannot confidently rely on the value of a single (or several) certain quality metrics.
Cite as

Simon van Wageningen, Tamara Mchedlidze, and Alexandru C. Telea. Same Quality Metrics, Different Graph Drawings. In 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 357, pp. 7:1-7:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{vanwageningen_et_al:LIPIcs.GD.2025.7,
  author =	{van Wageningen, Simon and Mchedlidze, Tamara and Telea, Alexandru C.},
  title =	{{Same Quality Metrics, Different Graph Drawings}},
  booktitle =	{33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)},
  pages =	{7:1--7:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-403-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{357},
  editor =	{Dujmovi\'{c}, Vida and Montecchiani, Fabrizio},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GD.2025.7},
  URN =		{urn:nbn:de:0030-drops-249935},
  doi =		{10.4230/LIPIcs.GD.2025.7},
  annote =	{Keywords: graph drawing, quality metrics, assumptions, fooling}
}
Document
DOI: 10.4230/LIPIcs.GD.2025.39
Optimizing Wiggle in Storylines

Authors: Alexander Dobler, Tim Hegemann, Martin Nöllenburg, and Alexander Wolff

Published in: LIPIcs, Volume 357, 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)

Abstract
A storyline visualization shows interactions between characters over time. Each character is represented by an x-monotone curve. Time is mapped to the x-axis, and groups of characters that interact at a particular point t in time must be ordered consecutively in the y-dimension at x = t. The predominant objective in storyline optimization so far has been the minimization of crossings between (blocks of) characters. Building on this work, we investigate another important, but less studied quality criterion, namely the minimization of wiggle, i.e., the amount of vertical movement of the characters over time. Given a storyline instance together with an ordering of the characters at any point in time, we show that wiggle count minimization is NP-complete. In contrast, we provide algorithms based on mathematical programming to solve linear wiggle height minimization and quadratic wiggle height minimization efficiently. Finally, we introduce a new method for routing character curves that focuses on keeping distances between neighboring curves constant as long as they run in parallel. We have implemented our algorithms, and we conduct a case study that explores the differences between the three optimization objectives. We use existing benchmark data, but we also present a new use case for storylines, namely the visualization of rolling stock schedules in railway operation.
Cite as

Alexander Dobler, Tim Hegemann, Martin Nöllenburg, and Alexander Wolff. Optimizing Wiggle in Storylines. In 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 357, pp. 39:1-39:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{dobler_et_al:LIPIcs.GD.2025.39,
  author =	{Dobler, Alexander and Hegemann, Tim and N\"{o}llenburg, Martin and Wolff, Alexander},
  title =	{{Optimizing Wiggle in Storylines}},
  booktitle =	{33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)},
  pages =	{39:1--39:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-403-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{357},
  editor =	{Dujmovi\'{c}, Vida and Montecchiani, Fabrizio},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GD.2025.39},
  URN =		{urn:nbn:de:0030-drops-250252},
  doi =		{10.4230/LIPIcs.GD.2025.39},
  annote =	{Keywords: Storyline visualization, wiggle minimization, NP-complete, linear programming, quadratic programming, experimental analysis}
}
Document
DOI: 10.4230/LIPIcs.GD.2025.38
Stress in Graph Drawings: Perception, Preference, and Performance

Authors: Gavin J. Mooney, Jacob Miller, Michael Wybrow, Stephen Kobourov, and Helen C. Purchase

Published in: LIPIcs, Volume 357, 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)

Abstract
Stress in a graph drawing has been a popular layout principle for more than two decades. Low stress drawings exhibit the property that the geometric distances between all pairs of nodes correlate with the shortest paths between them. The assumption has always been that low stress drawings are "nicer" and better support human perception and comprehension than high stress drawings. In this paper, we put these assumptions to the test. We use a normalised scale-independent and rotation-independent metric for stress; this is necessary to ensure strict controls on our experimental stimuli. We report on three experiments, exploring human perception of stress, preference for stress, and the effect of stress on a graph performance task. We conclude that people can see stress in a graph drawing, that they prefer low stress drawings, and that their performance in a shortest path task improves as stress decreases - thus empirically confirming long-standing assumptions.
Cite as

Gavin J. Mooney, Jacob Miller, Michael Wybrow, Stephen Kobourov, and Helen C. Purchase. Stress in Graph Drawings: Perception, Preference, and Performance. In 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 357, pp. 38:1-38:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{mooney_et_al:LIPIcs.GD.2025.38,
  author =	{Mooney, Gavin J. and Miller, Jacob and Wybrow, Michael and Kobourov, Stephen and Purchase, Helen C.},
  title =	{{Stress in Graph Drawings: Perception, Preference, and Performance}},
  booktitle =	{33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)},
  pages =	{38:1--38:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-403-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{357},
  editor =	{Dujmovi\'{c}, Vida and Montecchiani, Fabrizio},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GD.2025.38},
  URN =		{urn:nbn:de:0030-drops-250240},
  doi =		{10.4230/LIPIcs.GD.2025.38},
  annote =	{Keywords: Graph Drawing, Graph Drawing Metrics, Stress, Visual Perception, User Study}
}
Document
DOI: 10.4230/LIPIcs.GD.2025.37
Show Me Your Best Side: Characteristics of User-Preferred Perspectives for 3D Graph Drawings

Authors: Lucas Joos, Gavin J. Mooney, Maximilian T. Fischer, Daniel A. Keim, Falk Schreiber, Helen C. Purchase, and Karsten Klein

Published in: LIPIcs, Volume 357, 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)

Abstract
The visual analysis of graphs in 3D has become increasingly popular, accelerated by the rise of immersive technology, such as augmented and virtual reality. Unlike 2D drawings, 3D graph layouts are highly viewpoint-dependent, making perspective selection critical for revealing structural and relational patterns. Despite its importance, there is limited empirical evidence guiding what constitutes an effective or preferred viewpoint from the user’s perspective. In this paper, we present a systematic investigation into user-preferred viewpoints in 3D graph visualisations. We conducted a controlled study with 23 participants in a virtual reality environment, where users selected their most and least preferred viewpoints for 36 different graphs varying in size and layout. From this data, enriched by qualitative feedback, we distil common strategies underlying viewpoint choice. We further analyse the alignment of user preferences with classical 2D aesthetic criteria (e.g., Crossings), 3D-specific measures (e.g., Node-Node Occlusion), and introduce a novel measure capturing the perceivability of a graph’s principal axes (Isometric Viewpoint Deviation). Our data-driven analysis indicates that Stress, Crossings, Gabriel Ratio, Edge-Node Overlap, and Isometric Viewpoint Deviation are key indicators of viewpoint preference. Beyond our findings, we contribute a publicly available dataset consisting of the graphs and computed aesthetic measures, supporting further research and the development of viewpoint evaluation measures for 3D graph drawing.
Cite as

Lucas Joos, Gavin J. Mooney, Maximilian T. Fischer, Daniel A. Keim, Falk Schreiber, Helen C. Purchase, and Karsten Klein. Show Me Your Best Side: Characteristics of User-Preferred Perspectives for 3D Graph Drawings. In 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 357, pp. 37:1-37:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{joos_et_al:LIPIcs.GD.2025.37,
  author =	{Joos, Lucas and Mooney, Gavin J. and Fischer, Maximilian T. and Keim, Daniel A. and Schreiber, Falk and Purchase, Helen C. and Klein, Karsten},
  title =	{{Show Me Your Best Side: Characteristics of User-Preferred Perspectives for 3D Graph Drawings}},
  booktitle =	{33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)},
  pages =	{37:1--37:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-403-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{357},
  editor =	{Dujmovi\'{c}, Vida and Montecchiani, Fabrizio},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GD.2025.37},
  URN =		{urn:nbn:de:0030-drops-250236},
  doi =		{10.4230/LIPIcs.GD.2025.37},
  annote =	{Keywords: Graph Aesthetics, Immersive 3D, Node-Link Diagrams, Empirical Evaluation}
}
Document
Poster Abstract
DOI: 10.4230/LIPIcs.GD.2025.54
BH-tsNET, FIt-tsNET, L-tsNET: Fast tsNET Algorithms for Large Graph Drawing (Poster Abstract)

Authors: Amyra Meidiana, Seok-Hee Hong, and Kwan-Liu Ma

Published in: LIPIcs, Volume 357, 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)

Abstract
The tsNET algorithm adapts the popular dimensional reduction method t-SNE for graph drawing to compute high-quality drawings, preserving the neighborhood and clustering structure. However, its O(nm) runtime results in poor scalability for large graphs. In this poster, we present three fast algorithms for reducing the time complexity of tsNET to O(n log n) time and O(n) time, by integrating new fast methods for computation of high-dimensional probabilities and entropy computation with fast t-SNE algorithms for computation of KL divergence gradient. Specifically, we present two O(n log n)-time algorithms BH-tsNET and FIt-tsNET, incorporating partial BFS-based high-dimensional probability computation and a new quadtree-based entropy computation with fast t-SNE algorithms, and O(n)-time algorithm L-tsNET, introducing a new fast interpolation-based entropy computation. Extensive experiments using benchmark data sets confirm that BH-tsNET, FIt-tsNET, and L-tsNET outperform tsNET, achieving 93.5%, 96%, and 98.6% faster runtime, respectively, while computing similar quality drawings in terms of quality metrics (neighborhood preservation, stress, shape-based metrics, and edge crossing) and visual comparison.
Cite as

Amyra Meidiana, Seok-Hee Hong, and Kwan-Liu Ma. BH-tsNET, FIt-tsNET, L-tsNET: Fast tsNET Algorithms for Large Graph Drawing (Poster Abstract). In 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 357, pp. 54:1-54:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{meidiana_et_al:LIPIcs.GD.2025.54,
  author =	{Meidiana, Amyra and Hong, Seok-Hee and Ma, Kwan-Liu},
  title =	{{BH-tsNET, FIt-tsNET, L-tsNET: Fast tsNET Algorithms for Large Graph Drawing}},
  booktitle =	{33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)},
  pages =	{54:1--54:5},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-403-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{357},
  editor =	{Dujmovi\'{c}, Vida and Montecchiani, Fabrizio},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GD.2025.54},
  URN =		{urn:nbn:de:0030-drops-250400},
  doi =		{10.4230/LIPIcs.GD.2025.54},
  annote =	{Keywords: tsNET, t-SNE, Large Graph Drawing}
}
Artifact
Software
DOI: 10.4230/artifacts.25058
NNP-NET

Authors: Ilan Hartskeerl, Tamara Mchedlidze, Simon van Wageningen, Peter Vangorp, and Alexandru Telea

Abstract
Cite as

Ilan Hartskeerl, Tamara Mchedlidze, Simon van Wageningen, Peter Vangorp, Alexandru Telea. NNP-NET (Software, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@misc{software_nnpnet,
   title = {{NNP-NET}}, 
   author = {Hartskeerl, Ilan and Mchedlidze, Tamara and van Wageningen, Simon and Vangorp, Peter and Telea, Alexandru},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:539da3e3adda73abc8bb1af0c2a5c59fb7abef49;origin=https://github.com/IlanHartskeerl/NNP-NET;visit=swh:1:snp:cc28063a07356e46bb4d2ca85ac1e7098c891196;anchor=swh:1:rev:7baafec7993065930575f63f4697ee575bb05f0a}{\texttt{swh:1:dir:539da3e3adda73abc8bb1af0c2a5c59fb7abef49}} (visited on 2025-11-26)},
   url = {https://github.com/IlanHartskeerl/NNP-NET},
   doi = {10.4230/artifacts.25058},
}
Document
DOI: 10.4230/DagSemProc.09211.4
Comparison of Node-Link and Hierarchical Edge Bundling Layouts: A User Study

Authors: Alexandru Telea, Ozan Ersoy, Hessel Hoogendorp, and Dennie Reniers

Published in: Dagstuhl Seminar Proceedings, Volume 9211, Visualization and Monitoring of Network Traffic (2009)

Abstract
Visually investigating large network-like structures is a challenging task. Several approaches have been proposed in the past: node-link diagrams, adjacency matrices, and, more recently, hierarchical edge bundles. We present a recent experiment that compares the effectiveness of the classical node-link diagrams with the more recent hierarchical bundled edges. The users involved several computer science practitioners, the data ranged from graphs of several hundreds to several tens of hundreds of nodes, the tasks involved answering a number of structural overview as well as detailed questions involved system dependencies.
Cite as

Alexandru Telea, Ozan Ersoy, Hessel Hoogendorp, and Dennie Reniers. Comparison of Node-Link and Hierarchical Edge Bundling Layouts: A User Study. In Visualization and Monitoring of Network Traffic. Dagstuhl Seminar Proceedings, Volume 9211, pp. 1-12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{telea_et_al:DagSemProc.09211.4,
  author =	{Telea, Alexandru and Ersoy, Ozan and Hoogendorp, Hessel and Reniers, Dennie},
  title =	{{Comparison of Node-Link and Hierarchical Edge Bundling Layouts: A User Study}},
  booktitle =	{Visualization and Monitoring of Network Traffic},
  pages =	{1--12},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9211},
  editor =	{Daniel A. Keim and Aiko Pras and J\"{u}rgen Sch\"{o}nw\"{a}lder and Pak Chung Wong},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09211.4},
  URN =		{urn:nbn:de:0030-drops-21542},
  doi =		{10.4230/DagSemProc.09211.4},
  annote =	{Keywords: Graph visualization, user studies, software visualization, call graphs}
}
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