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Record W4246877953 · doi:10.4018/9781931777476.ch015

On the Computation of Recursion in Relational Databases

2011· book-chapter· en· W4246877953 on OpenAlex
Yangjun Chen

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

VenueIGI Global eBooks · 2011
Typebook-chapter
Languageen
FieldComputer Science
TopicAdvanced Database Systems and Queries
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsRecursion (computer science)Computer scienceRelational databaseDirected acyclic graphGraph databaseComputationGraphTheoretical computer scienceDirected graphDatabaseRelational database management systemAlgorithmProgramming language

Abstract

fetched live from OpenAlex

A composite object represented as a directed graph is an important data structure which requires efficient support in CAD/CAM, CASE, office systems, software management, Web databases and document databases. It is cumbersome to handle such an object in relational database systems when it involves recursive relationships. In this chapter, we present a new encoding method to support the efficient computation of recursion. In addition, we devise a linear time algorithm to identify a sequence of reachable trees (w.r.t.) a directed acyclic graph (DAG), which covers all the edges of the graph. Together with the new encoding method, this algorithm enables us to compute recursion w.r.t. a DAG in time O(e), where e represents the number of edges of the DAG. More importantly, this method is especially suitable for a relational environment.

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: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.726
Threshold uncertainty score0.579

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 communication0.0000.000
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 head0.054
GPT teacher head0.267
Teacher spread0.214 · 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