@inproceedings{01J46HHCSC4GX2NKRPZXTTQXVC,
  abstract     = {{Traversal-based query execution enables the resolving of
queries over Linked Data documents, using a follow-your-nose approach
to locating query-relevant data by following series of links through documents. This traversal, however, incurs an unavoidable overhead in the form
of data access costs. Through only following links known to be relevant
for answering a given query, this overhead could be minimized. Prior
work exists in the form of reachability conditions to determine the links
to dereference, however this does not take into consideration the contents
behind a given link. Within this work, we have explored the possibility
of using Bloom filters to prune query-irrelevant links based on the triple
patterns contained within a given query, when performing traversal-based
query execution over Solid pods containing simulated social network data
as an example use case. Our discoveries show that, with relatively uniform
data across an entire benchmark dataset, this approach fails to effectively
filter links, especially when the queries contain triple patterns with low
selectivity. Thus, future work should consider the query plan beyond
individual patterns, or the structure of the data beyond individual triples,
to allow for more effective pruning of links}},
  author       = {{Hanski, Jonni and Taelman, Ruben and Verborgh, Ruben}},
  booktitle    = {{SEMANTIC WEB : ESWC 2024 SATELLITE EVENTS, PT I}},
  isbn         = {{9783031789519}},
  issn         = {{0302-9743}},
  language     = {{eng}},
  location     = {{Hersonissos, Greece}},
  pages        = {{228--233}},
  title        = {{Observations on bloom filters for traversal-based query execution over solid pods}},
  url          = {{http://doi.org/10.1007/978-3-031-78952-6_32}},
  volume       = {{15344}},
  year         = {{2025}},
}

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