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Federated knowledge graph partitioning strategies analyzed in new research

By PulseAugur Editorial · [1 sources] ·

A new research paper explores the impact of different partitioning strategies on vertically partitioned federated knowledge graphs. The study formalizes vertical partitioning as a design space and compares four strategies: semantic domain grouping, frequency-balanced partitioning, co-occurrence graph-cut partitioning, and random partitioning. Experiments using the MetaQA and PathQuestion datasets revealed a trade-off between locality and balance, which is influenced by the number of silos and the capacity of each silo to hold multiple relations. AI

IMPACT Provides practical guidance for optimizing federated knowledge graph deployments by analyzing partitioning strategies.

RANK_REASON The cluster contains a research paper published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Federated knowledge graph partitioning strategies analyzed in new research

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The cluster contains a research paper published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Md Saikat Islam Khan Bappy, Oshani Seneviratne ·

    Cost Characterization of Vertically Partitioned Federated Knowledge Graphs

    arXiv:2609.13664v1 Announce Type: new Abstract: Knowledge graphs are increasingly distributed across autonomous organizations that share an entity space but own disjoint subsets of relations, forming a vertical partition. Answering a multi-hop query may require combining facts fr…

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