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Record W101317446

A Data Locating Mechanism for Distributed XML Data over P2P Networks

2004· article· en· W101317446 on OpenAlexaff
Qiang Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicPeer-to-Peer Network Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceStreaming XMLEfficient XML InterchangeXML databaseScalabilityXML SignatureDistributed computingXPathOverlay networkXMLComputer networkXML EncryptionFlooding (psychology)The InternetDatabaseWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

Many emerging applications that use XML are distributed, usually over the Internet or over large Peer-to-Peer (P2P) networks. A fundamental problem of XML query processing in these systems is how to locate the data relevant to the queries so that only useful data are involved in query evaluation. In this paper, we address this problem within the context of structured P2P networks, and propose a novel data locating mechanism for query shipping systems. Our approach follows the multi-hop routing approach and encodes the hierarchical information of the XML data into the overlay network, so that routing keys can be hierarchical XML path expressions. We also propose a decentralized data locating algorithm that does not employ a centralized catalog but also avoids flooding the network with XML queries. We report comprehensive experiments to demonstrate the scalability and effectiveness of the data locating mechanism. 1

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.912
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0120.012
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.074
GPT teacher head0.309
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2004
Admission routes1
Has abstractyes

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