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Record W2017668371 · doi:10.3166/ria.22.137-159

Génération de plan de site web pour les non-voyants par des fourmis artificielles

2008· article· fr· W2017668371 on OpenAlexvenueno aff
Sonia Nicolas, Nicolas Monmarché, Mohamed Slimane

Bibliographic record

VenueRevue d intelligence artificielle · 2008
Typearticle
Languagefr
FieldComputer Science
TopicData Management and Algorithms
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesBiologyPhilosophy

Abstract

fetched live from OpenAlex

Face aux problemes de navigation que rencontrent les internautes notamment a cause de la multitude des pages et des liens, nous proposons dans cet article un generateur de plan de site web. Utilisable par les internautes mais egalement par les webmestres, les plans de sites obtenus presentent la particularite de s'adapter aux capacites de memorisation des personnes handicapees visuelles. Dans cet article nous presentons notre methode de generation de plan qui utilise des fourmis artificielles afin de creer des regroupements de pages web semantiquement proche, puis qui execute l'algorithme de Prim sur chacun des regroupements realises par les fourmis artificielles.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.761
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.004

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 head0.124
GPT teacher head0.277
Teacher spread0.153 · 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; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations0
Published2008
Admission routes1
Has abstractyes

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