research-article

Understanding Missing Links in Bipartite Networks With MissBiN

Authors:

Patrick ChiuAuthors Info & Claims

IEEE Transactions on Visualization and Computer Graphics, Volume 28, Issue 6

Pages 2457 - 2469

https://doi.org/10.1109/TVCG.2020.3032984

Published: 01 June 2022 Publication History

Abstract

The analysis of bipartite networks is critical in a variety of application domains, such as exploring entity co-occurrences in intelligence analysis and investigating gene expression in bio-informatics. One important task is missing link prediction, which infers the existence of unseen links based on currently observed ones. In this article, we propose a visual analysis system, MissBiN, to involve analysts in the loop for making sense of link prediction results. MissBiN equips a novel method for link prediction in a bipartite network by leveraging the information of bi-cliques in the network. It also provides an interactive visualization for understanding the algorithm outputs. The design of MissBiN is based on three high-level analysis questions (what, why, and how) regarding missing links, which are distilled from the literature and expert interviews. We conducted quantitative experiments to assess the performance of the proposed link prediction algorithm, and interviewed two experts from different domains to demonstrate the effectiveness of MissBiN as a whole. We also provide a comprehensive usage scenario to illustrate the usefulness of the tool in an application of intelligence analysis.

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Cited By

Sun MWang YBolton CMa YLi TZhao J(2024)Investigating User Estimation of Missing Data in Visual AnalysisProceedings of the 50th Graphics Interface Conference10.1145/3670947.3670977(1-13)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3670947.3670977
Sun MShaikh AAlhoori HZhao J(2021)SightBi: Exploring Cross-View Data Relationships with BiclustersIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.311480128:1(54-64)Online publication date: 24-Dec-2021
https://dl.acm.org/doi/10.1109/TVCG.2021.3114801

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Understanding Missing Links in Bipartite Networks With MissBiN

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cover image IEEE Transactions on Visualization and Computer Graphics

IEEE Transactions on Visualization and Computer Graphics Volume 28, Issue 6

June 2022

251 pages

ISSN:1077-2626

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1077-2626 © 2020 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.

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Published: 01 June 2022

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Cited By

Sun MWang YBolton CMa YLi TZhao J(2024)Investigating User Estimation of Missing Data in Visual AnalysisProceedings of the 50th Graphics Interface Conference10.1145/3670947.3670977(1-13)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3670947.3670977
Sun MShaikh AAlhoori HZhao J(2021)SightBi: Exploring Cross-View Data Relationships with BiclustersIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.311480128:1(54-64)Online publication date: 24-Dec-2021
https://dl.acm.org/doi/10.1109/TVCG.2021.3114801

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