A Fast Hop-Biased Approximation Algorithm for the Quadratic Group Steiner Tree Problem
Authors: 
Xiaoqing Wang, 
Gong ChengAuthors Info & Claims
Xiaoqing Wang, Gong ChengAuthors Info & ClaimsPages 312 - 321
Abstract
Knowledge Graph (KG) exploration helps Web users understand the contents of a large and unfamiliar KG and extract relevant insights. The task has recently been formulated as a Quadratic Group Steiner Tree Problem (QGSTP) to search for a semantically cohesive subgraph connecting entities that match query keywords. However, on large graphs, existing algorithms for this NP-hard problem cannot meet the performance need. In this paper, we propose a novel approximation algorithm for QGSTP called HB. It finds and merges an optimal set of paths according to a Hop-Biased objective function, which not only leads to a guaranteed approximation ratio but is also decomposable by paths to enable efficient dynamic programming based search. Accompanied by a set of pruning heuristics, HB outperformed the state of the art by 1-2 orders of magnitude, empirically reducing the average time for answering a query on a million-scale graph from about one minute to one second.
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- A Fast Hop-Biased Approximation Algorithm for the Quadratic Group Steiner Tree Problem
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Published In
May 2024
4826 pages
ISBN:9798400701719
DOI:10.1145/3589334
- General Chairs:
- Tat-Seng Chua,
- Chong-Wah Ngo,
- Proceedings Chair:
- Roy Ka-Wei Lee,
- Program Chairs:
- Ravi Kumar,
- Hady W. Lauw
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Published: 13 May 2024
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