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Record W2115844906 · doi:10.1109/ideas.2007.6

A Generalized Model for Mediator Based Information Integration

2007· article· en· W2115844906 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Database Engineering and Applications Symposium · 2007
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Database Systems and Queries
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer scienceSchema (genetic algorithms)Information integrationTheoretical computer scienceData integrationMetadataSemi-structured modelDimension (graph theory)Relational databaseData miningInformation retrievalMathematicsDatabase modelPure mathematics

Abstract

fetched live from OpenAlex

Heterogeneity of schema and data in information integration complicates metadata management and query processing. We consider a mediator-based approach (MI) to information integration and propose a model theoretic approach to describe integration. In this model, we view the schema of the integration as a 3D space, and assume it is a complete lattice. The first dimension in the model specifies the concepts (e.g., entity sets, relations, classes, etc), the second dimension indicates the data model in which a concept is represented (e.g., relational, semi-structured, object-oriented, etc), and the third dimension gives the application domain. We also introduce three basic transformations, called X-transform, Y-transform, and Z-transform, to all of which we refer as primitive queries and show how user queries can be expressed using primitive queries. We show a typical architecture and illustrate usefulness of this model as it generalizes the mediator based information integration in which the global schema is basically the least upper bound of all the points in the 3D space.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.932
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.244
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