Top-k query evaluation for schema-based peer-to-peer networks

Research output: Chapter in book/report/conference proceedingContribution to book/anthologyResearchpeer review

Authors

Research Organisations

External Research Organisations

  • University of California at Berkeley
View graph of relations

Details

Original languageEnglish
Title of host publicationThe Semantic Web
Subtitle of host publicationISWC 2004
EditorsSheila A. McIlraith, Dimitris Plexousakis, Frank van Harmelen
PublisherSpringer Verlag
Pages137-151
Number of pages15
ISBN (electronic)978-3-540-30475-3
ISBN (print)978-3-540-23798-3
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3298
ISSN (Print)0302-9743
ISSN (electronic)1611-3349

Abstract

Increasing the number of peers in a peer-to-peer network usually increases the number of answers to a given query as well. While having more answers is nice in principle, users are not interested in arbitrarily large and unordered answer sets, but rather in a small set of "best" answers. Inspired by the success of ranking algorithms in Web search engine and top-k query evaluation algorithms in databases, we propose a decentralized top-k query evaluation algorithm for peer-to-peer networks which makes use of local rankings, rank merging and optimized routing based on peer ranks, and minimizes both answer set size and network traffic among peers. As our algorithm is based on dynamically collected query statistics only, no continuous index update processes are necessary, allowing it to scale easily to large numbers of peers.

Keywords

    Peer-to-peer query processing, Ranking, Top-k retrieval

ASJC Scopus subject areas

Cite this

Top-k query evaluation for schema-based peer-to-peer networks. / Nejdl, Wolfgang; Siberski, Wolf; Thaden, Uwe et al.
The Semantic Web: ISWC 2004. ed. / Sheila A. McIlraith; Dimitris Plexousakis; Frank van Harmelen. Springer Verlag, 2004. p. 137-151 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3298).

Research output: Chapter in book/report/conference proceedingContribution to book/anthologyResearchpeer review

Nejdl, W, Siberski, W, Thaden, U & Balke, WT 2004, Top-k query evaluation for schema-based peer-to-peer networks. in SA McIlraith, D Plexousakis & F van Harmelen (eds), The Semantic Web: ISWC 2004. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3298, Springer Verlag, pp. 137-151. https://doi.org/10.1007/978-3-540-30475-3_11
Nejdl, W., Siberski, W., Thaden, U., & Balke, W. T. (2004). Top-k query evaluation for schema-based peer-to-peer networks. In S. A. McIlraith, D. Plexousakis, & F. van Harmelen (Eds.), The Semantic Web: ISWC 2004 (pp. 137-151). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3298). Springer Verlag. https://doi.org/10.1007/978-3-540-30475-3_11
Nejdl W, Siberski W, Thaden U, Balke WT. Top-k query evaluation for schema-based peer-to-peer networks. In McIlraith SA, Plexousakis D, van Harmelen F, editors, The Semantic Web: ISWC 2004. Springer Verlag. 2004. p. 137-151. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-30475-3_11
Nejdl, Wolfgang ; Siberski, Wolf ; Thaden, Uwe et al. / Top-k query evaluation for schema-based peer-to-peer networks. The Semantic Web: ISWC 2004. editor / Sheila A. McIlraith ; Dimitris Plexousakis ; Frank van Harmelen. Springer Verlag, 2004. pp. 137-151 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Download
@inbook{03e89a1d82564b6f8ec2a74067eaee0b,
title = "Top-k query evaluation for schema-based peer-to-peer networks",
abstract = "Increasing the number of peers in a peer-to-peer network usually increases the number of answers to a given query as well. While having more answers is nice in principle, users are not interested in arbitrarily large and unordered answer sets, but rather in a small set of {"}best{"} answers. Inspired by the success of ranking algorithms in Web search engine and top-k query evaluation algorithms in databases, we propose a decentralized top-k query evaluation algorithm for peer-to-peer networks which makes use of local rankings, rank merging and optimized routing based on peer ranks, and minimizes both answer set size and network traffic among peers. As our algorithm is based on dynamically collected query statistics only, no continuous index update processes are necessary, allowing it to scale easily to large numbers of peers.",
keywords = "Peer-to-peer query processing, Ranking, Top-k retrieval",
author = "Wolfgang Nejdl and Wolf Siberski and Uwe Thaden and Balke, {Wolf Tilo}",
year = "2004",
doi = "10.1007/978-3-540-30475-3_11",
language = "English",
isbn = "978-3-540-23798-3",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "137--151",
editor = "McIlraith, {Sheila A.} and Dimitris Plexousakis and {van Harmelen}, Frank",
booktitle = "The Semantic Web",
address = "Germany",

}

Download

TY - CHAP

T1 - Top-k query evaluation for schema-based peer-to-peer networks

AU - Nejdl, Wolfgang

AU - Siberski, Wolf

AU - Thaden, Uwe

AU - Balke, Wolf Tilo

PY - 2004

Y1 - 2004

N2 - Increasing the number of peers in a peer-to-peer network usually increases the number of answers to a given query as well. While having more answers is nice in principle, users are not interested in arbitrarily large and unordered answer sets, but rather in a small set of "best" answers. Inspired by the success of ranking algorithms in Web search engine and top-k query evaluation algorithms in databases, we propose a decentralized top-k query evaluation algorithm for peer-to-peer networks which makes use of local rankings, rank merging and optimized routing based on peer ranks, and minimizes both answer set size and network traffic among peers. As our algorithm is based on dynamically collected query statistics only, no continuous index update processes are necessary, allowing it to scale easily to large numbers of peers.

AB - Increasing the number of peers in a peer-to-peer network usually increases the number of answers to a given query as well. While having more answers is nice in principle, users are not interested in arbitrarily large and unordered answer sets, but rather in a small set of "best" answers. Inspired by the success of ranking algorithms in Web search engine and top-k query evaluation algorithms in databases, we propose a decentralized top-k query evaluation algorithm for peer-to-peer networks which makes use of local rankings, rank merging and optimized routing based on peer ranks, and minimizes both answer set size and network traffic among peers. As our algorithm is based on dynamically collected query statistics only, no continuous index update processes are necessary, allowing it to scale easily to large numbers of peers.

KW - Peer-to-peer query processing

KW - Ranking

KW - Top-k retrieval

UR - http://www.scopus.com/inward/record.url?scp=35048901002&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-30475-3_11

DO - 10.1007/978-3-540-30475-3_11

M3 - Contribution to book/anthology

AN - SCOPUS:35048901002

SN - 978-3-540-23798-3

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 137

EP - 151

BT - The Semantic Web

A2 - McIlraith, Sheila A.

A2 - Plexousakis, Dimitris

A2 - van Harmelen, Frank

PB - Springer Verlag

ER -

By the same author(s)