Noisy Interactive Graph Search: An Uncertainty-Based Approach with Online Modeling of Latent Expertise and Difficulty
Summary: IGS-RTA formulates noisy interactive graph search via global search uncertainty, selecting queries by expected uncertainty reduction with logarithmic query complexity. It jointly models and learns latent oracle expertise and task difficulty online, improving accuracy up to 52% and cutting costs 8×. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Han Linghu (Hong Kong University of Science and Technology)
- 2. Qianhao Cong (National University of Singapore)
- 3. Liang Feng (Chongqing University)
- 4. Lei Chen (Hong Kong University of Science and Technology)
- 5. Jing Tang (Hong Kong University of Science and Technology)
BibTeX Citation
@article{linghu_vldb26,
title = {{Noisy Interactive Graph Search: An Uncertainty-Based Approach with Online Modeling of Latent Expertise and Difficulty}},
author = {Linghu, Han and Cong, Qianhao and Feng, Liang and Chen, Lei and Tang, Jing},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {11},
pages = {3119--3132},
doi = {10.14778/3836663.3836677},
url = {https://doi.org/10.14778/3836663.3836677},
year = {2026}
}
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