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Record W1515505871

An interactive system for recognizing hand drawn UML diagrams

2000· article· en· W1515505871 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

VenueConference of the Centre for Advanced Studies on Collaborative Research · 2000
Typearticle
Languageen
FieldComputer Science
TopicModel-Driven Software Engineering Techniques
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer scienceUnified Modeling LanguageUML toolApplications of UMLProgramming languageClass diagramNotationArtificial intelligenceSoftware
DOInot available

Abstract

fetched live from OpenAlex

Diagrams are widely used by software engineers to capture the structure and organization of software systems. The Unified Modeling Language (UML) is a commonly-used notation for such diagrams. We have designed and implemented a system for the on-line recognition of hand drawn UML diagrams. Input comes from an electronic whiteboard, a mouse, or a data tablet. A sophisticated segmentation algorithm groups pen strokes into symbols, coping with drawing inaccuracies that are common in hand drawn input. The system is organized around a retargetable kernel which provides a general front end for on-line recognition of any iconic notation. The kernel is extended with UML specific enhancements to segmentation, as well as UML specific glyph recognizers. A simple and intuitive graphical user interface allows the user to correct segmentation and recognition errors. Relatively messy freehand UML drawings are interpreted properly.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.856
Threshold uncertainty score0.718

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 communication0.0000.001
Open science0.0010.000
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 head0.091
GPT teacher head0.400
Teacher spread0.310 · 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