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View all- Bergami GMaggi FMontali MPeñaloza R(2021)A Tool for Computing Probabilistic Trace AlignmentsIntelligent Information Systems10.1007/978-3-030-79108-7_14(118-126)Online publication date: 15-Jun-2021
Hierarchical embedding for DAG reachability queries
Article No.: 24, Pages 1 - 10
Abstract
Current hierarchical embeddings are inaccurate in both reconstructing the original taxonomy and answering reachability queries over Direct Acyclic Graph. In this paper, we propose a new hierarchical embedding, the Euclidean Embedding (EE), that is correct by design due to its mathematical formulation and associated lemmas. Such embedding can be constructed during the visit of a taxonomy, thus making it faster to generate if compared to other learning-based embeddings. After proposing a novel set of metrics for determining the embedding accuracy with respect to the reachability queries, we compare our proposed embedding with state-of-the-art approaches using full trees from 3 to 1555 nodes and over a real-world Direct Acyclic Graph of 1170 nodes. The benchmark shows that EE outperforms our competitors in both accuracy and efficiency.
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Index Terms
- Hierarchical embedding for DAG reachability queries
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Published: 25 August 2020
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IDEAS 2020
IDEAS 2020: 24th International Database Engineering & Applications Symposium
August 12 - 14, 2020
Seoul, Republic of Korea
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IDEAS '20 Paper Acceptance Rate 27 of 57 submissions, 47%;
Overall Acceptance Rate 74 of 210 submissions, 35%
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View all- Bergami GMaggi FMontali MPeñaloza R(2021)A Tool for Computing Probabilistic Trace AlignmentsIntelligent Information Systems10.1007/978-3-030-79108-7_14(118-126)Online publication date: 15-Jun-2021
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