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Interactive visual clustering

Published: 28 January 2007 Publication History

Abstract

Interactive Visual Clustering (IVC) is a novel method that allows a user to explore relational data sets interactively, in order to produce a clustering that satisfies their objectives. IVC combines spring-embedded graph layout with user interaction and constrained clustering. Experimental results on several synthetic and real-world data sets show that IVC yields better clustering performance than alternative methods.

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Cited By

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  • (2024): A Cluster Ambiguity Measure for Estimating Perceptual Variability in Visual ClusteringIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.332720130:1(770-780)Online publication date: 1-Jan-2024
  • (2023)ModEx: a general purpose computer model exploration systemFrontiers in Bioinformatics10.3389/fbinf.2023.11538003Online publication date: 25-May-2023
  • (2023)Towards Addressing Ambiguous Interactions and Inferring User Intent with Dimension Reduction and Clustering Combinations in Visual AnalyticsACM Transactions on Interactive Intelligent Systems10.1145/3588565Online publication date: 17-Apr-2023
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Published In

cover image ACM Conferences
IUI '07: Proceedings of the 12th international conference on Intelligent user interfaces
January 2007
388 pages
ISBN:1595934812
DOI:10.1145/1216295
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 January 2007

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Author Tags

  1. clustering
  2. constraints
  3. interaction

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IUI07

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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Cited By

View all
  • (2024): A Cluster Ambiguity Measure for Estimating Perceptual Variability in Visual ClusteringIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.332720130:1(770-780)Online publication date: 1-Jan-2024
  • (2023)ModEx: a general purpose computer model exploration systemFrontiers in Bioinformatics10.3389/fbinf.2023.11538003Online publication date: 25-May-2023
  • (2023)Towards Addressing Ambiguous Interactions and Inferring User Intent with Dimension Reduction and Clustering Combinations in Visual AnalyticsACM Transactions on Interactive Intelligent Systems10.1145/3588565Online publication date: 17-Apr-2023
  • (2022)ConfLabeling: Assisting Image Labeling with User and System ConfidenceHCI International 2022 – Late Breaking Papers: Interacting with eXtended Reality and Artificial Intelligence10.1007/978-3-031-21707-4_26(357-376)Online publication date: 25-Nov-2022
  • (2021)SHIM: Semantic Hierarchical clustering with Interactive Machine learning2021 IEEE Workshop on Machine Learning from User Interactions (MLUI)10.1109/MLUI54255.2021.00007(12-20)Online publication date: Oct-2021
  • (2021)Bridging cognitive gaps between user and model in interactive dimension reductionVisual Informatics10.1016/j.visinf.2021.03.002Online publication date: Apr-2021
  • (2020)With respect to what?Proceedings of the 25th International Conference on Intelligent User Interfaces10.1145/3377325.3377516(177-188)Online publication date: 17-Mar-2020
  • (2020)Interactive ClusteringACM Computing Surveys10.1145/334096053:1(1-39)Online publication date: 6-Feb-2020
  • (2020)Interactive Assigning of Conference Sessions with Visualization and Topic Modeling2020 IEEE Pacific Visualization Symposium (PacificVis)10.1109/PacificVis48177.2020.1027x(236-240)Online publication date: Jun-2020
  • (2020)Interactive clustering: a scoping reviewArtificial Intelligence Review10.1007/s10462-020-09913-7Online publication date: 8-Oct-2020
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