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Record W1973214928 · doi:10.3166/isi.11.6.55-82

Sélection de schéma de fragmentation horizontale dans les entrepôts de données. Formalisation et algorithmes

2006· article· fr· W1973214928 on OpenAlex
Kamel Boukhalfa, Ladjel Bellatreche

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIngénierie des systèmes d information · 2006
Typearticle
Languagefr
FieldComputer Science
TopicAdvanced Database Systems and Queries
Canadian institutionsnot available
Fundersnot available
KeywordsComputer sciencePartition (number theory)Simulated annealingFragmentation (computing)AlgorithmMathematicsCombinatoricsOperating system

Abstract

fetched live from OpenAlex

Horizontal partitioning is a non redundant structure that reduces the query processing cost and facilitates the warehouse manageability. In order to partition a relational data warehouse, the best way consists in fragmenting dimension tables, then using their fragmentation schemas to partition the fact table. Selecting an optimal fragmentation solution is very costly. In this paper, the horizontal fragmentation selection problem is formalised as an optimisation problem with a maintenance constraint. We propose a hybrid method combining a genetic algorithm and a simulated annealing algorithm. Our experimental studies are based on APB-1 release II benchmark in order to validate our proposed algorithms.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.603
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.016
Open science0.0000.000
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 head0.022
GPT teacher head0.254
Teacher spread0.232 · 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