Matches in Ruben’s data for { ?s ?p ?o }
- publication maker ruben_eschauzier.
- publication maker meike_morren.
- publication maker me.
- publication title "Reinforcement Learning-based SPARQL Join Ordering Optimizer".
- publication isPartOf proceedings_of_the_20th_extended_semantic_web_conference.
- publication name "Reinforcement Learning-based SPARQL Join Ordering Optimizer".
- publication label "Reinforcement Learning-based SPARQL Join Ordering Optimizer".
- publication name "Reinforcement Learning-based SPARQL Join Ordering Optimizer".
- publication topic reuse.
- publication topic SPARQL.
- publication topic Research.
- publication topic RDF.
- publication subject reuse.
- publication subject SPARQL.
- publication subject Research.
- publication subject RDF.
- publication authorList b0_b1837.
- publication topic reuse.
- publication topic SPARQL.
- publication topic Research.
- publication topic RDF.
- publication abstract "In recent years, relational databases successfully leverage reinforcement learning to optimize query plans. For graph databases and RDF quad stores, such research has been limited, so there is a need to understand the impact of reinforcement learning techniques. We explore a reinforcement learning-based join plan optimizer that we design specifically for optimizing join plans during SPARQL query planning. This paper presents key aspects of this method and highlights open research problems. We argue that while we can reuse aspects of relational database optimization, SPARQL query optimization presents unique challenges not encountered in relational databases. Nevertheless, initial benchmarks show promising results that warrant further exploration.".
- publication datePublished "2023".
- publication mainEntityOfPage eschauzier_eswc_2023.
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- publication page eschauzier_eswc_2023.
- publication author me.
- publication author ruben_eschauzier.
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- publication creator me.
- publication creator ruben_eschauzier.
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- publication about access_control.
- publication about constraints.
- publication about Solid.
- publication about Research.
- publication about personal_data.
- publication author me.
- publication author ruben_eschauzier.
- publication author me.
- publication coparticipatesWith me.
- publication coparticipatesWith ruben_eschauzier.
- publication coparticipatesWith me.
- publication type ScholarlyArticle.
- publication type Article.
- publication type Document.
- publication type Q386724.
- publication type CreativeWork.
- publication type Document.
- publication type Work.
- publication type Document.
- publication P50 me.
- publication P50 ruben_eschauzier.
- publication P50 me.
- publication maker me.
- publication maker ruben_eschauzier.
- publication maker me.
- publication title "Revisiting Link Prioritization for Efficient Traversal in Structured Decentralized Environments".
- publication isPartOf proceedings_of_the_24th_international_semantic_web_conference.
- publication name "Revisiting Link Prioritization for Efficient Traversal in Structured Decentralized Environments".
- publication label "Revisiting Link Prioritization for Efficient Traversal in Structured Decentralized Environments".
- publication name "Revisiting Link Prioritization for Efficient Traversal in Structured Decentralized Environments".
- publication topic access_control.
- publication topic constraints.
- publication topic Solid.
- publication topic Research.
- publication topic personal_data.
- publication subject access_control.
- publication subject constraints.
- publication subject Solid.
- publication subject Research.
- publication subject personal_data.
- publication authorList b0_b1778.
- publication topic access_control.
- publication topic constraints.
- publication topic Solid.
- publication topic Research.
- publication topic personal_data.
- publication abstract "Decentralized environments distribute personal data across numerous small, independent data sources; a necessity driven by legal and socio-economic constraints that prevent the technologically more convenient central aggregation. Link Traversal-based Query Processing (LTQP) is a query technique that respects these constraints by iteratively discovering and accessing data sources while enabling fine-grained access control. Unfortunately, current LTQP implementations are slow due to limited prior knowledge of queried data and the high volume of HTTP requests required. Prioritizing data sources likely to lead to query-relevant data can improve query result arrival times. However, while link prioritization algorithms have been studied for Linked Open Data (LOD), their performance in structured decentralized environments remains untested. Evaluating this performance is essential to establish a baseline as a reference point for improving future implementations. We formally define the R3 metric to measure prioritization performance, extend it to continuous efficiency, and account for real-world scenarios. Furthermore, we provide modular and open-source implementations of the prioritization algorithms from the literature. Finally, using the R3 metric with existing metrics from the literature, we benchmark these link prioritization algorithms in a simulated Solid environment. In this paper, we report the benchmark results, provide a thorough analysis, and lessons learned for future work. We find that existing prioritization algorithms fail to improve performance in structured decentralized environments, with no non-oracle method outperforming the look-up order produced by a FIFO queue. We conclude that prioritization algorithms have little benefit in a structured decentralized environment, and recommend that research shift to pruning irrelevant links or improving the query plan.".
- publication mainEntityOfPage eschauzier_iswc_2025.
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- publication author agata_filipowska.
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- publication creator agata_filipowska.
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- publication author agata_filipowska.
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- publication coparticipatesWith me.
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- publication type ScholarlyArticle.
- publication type Article.