MLN-geeWhiz: A Dashboard for Supporting Complete Life-Cycle of Complex Data Analysis using Multilayer Networks
Summary: MLN-geeWhiz: an interactive web dashboard for the complete life-cycle of multilayer network (MLN) analytics — supports layer generation, cross-layer analysis, drill-down and visualization for heterogeneous entities/relations. Demonstrates architecture, capabilities and use cases (e.g., accident pattern and cross-platform influence analysis) to streamline exploratory MLN workflows from raw data to interpretable insights. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Amey Shinde (University of Texas)
- 2. Viraj Sabhaya (University of Texas)
- 3. Kevin Farokhrouz (University of Texas)
- 4. Fariba Irany (University of North Texas)
- 5. Ali Khan (University of North Texas)
- 6. Sanjukta Bhowmick (University of North Texas)
- 7. Abhishek Santra (University of Texas)
- 8. Sharma Chakravarthy (University of Texas)
BibTeX Citation
@article{shinde_vldb25,
title = {{MLN-geeWhiz: A Dashboard for Supporting Complete Life-Cycle of Complex Data Analysis using Multilayer Networks}},
author = {Shinde, Amey and Sabhaya, Viraj and Farokhrouz, Kevin and Irany, Fariba and Khan, Ali and Bhowmick, Sanjukta and Santra, Abhishek and Chakravarthy, Sharma},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {12},
pages = {5323--5326},
doi = {10.14778/3750601.3750662},
url = {https://doi.org/10.14778/3750601.3750662},
year = {2025}
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