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Abstract
Despite the prospect of a vast Web of interlinked data, the Semantic Web today mostly fails to meet its potential. One of the main problems it faces is rooted in its current architecture, which totally relies on the availability of the servers providing access to the data. These servers are subject to failures, which often results in situations where some data is unavailable. Recent advances have proposed decentralized peer-to-peer based architectures to alleviate this problem. However, for query processing these approaches mostly rely on flooding, a standard technique for peer-to-peer systems, which can easily result in very high network traffic and hence cause high query response times. To still enable efficient query processing in such networks, this paper proposes two indexing schemes, which in a decentralized fashion aim at efficiently finding nodes with relevant data for a given query: Locational Indexes and Prefix-Partitioned Bloom Filters. Our experiments show that such indexing schemes are able to considerably speed up query processing times compared to existing approaches.
Original language | English |
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Title of host publication | The Semantic Web – ISWC 2019 - 18th International Semantic Web Conference, Proceedings |
Editors | Chiara Ghidini, Olaf Hartig, Maria Maleshkova, Vojtech Svátek, Isabel Cruz, Aidan Hogan, Jie Song, Maxime Lefrançois, Fabien Gandon |
Number of pages | 18 |
Publisher | Springer |
Publication date | 2019 |
Pages | 3-20 |
ISBN (Print) | 978-3-030-30792-9 |
ISBN (Electronic) | 978-3-030-30793-6 |
DOIs | |
Publication status | Published - 2019 |
Event | The 18th International Semantic Web Conference, ISWC 2019 - Auckland, New Zealand Duration: 26 Oct 2019 → 30 Oct 2019 Conference number: 18th https://iswc2019.semanticweb.org/ |
Conference
Conference | The 18th International Semantic Web Conference, ISWC 2019 |
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Number | 18th |
Country/Territory | New Zealand |
City | Auckland |
Period | 26/10/2019 → 30/10/2019 |
Internet address |
Series | Lecture Notes in Computer Science |
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Volume | 11778 |
ISSN | 0302-9743 |
Fingerprint
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Poul Due Jensen Professorate in Big Data and Artificial Intelligence
Hose, K., Jendal, T. E. & Hansen, E. R.
01/11/2019 → 31/10/2024
Project: Research
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