Ontology-based negotiation protocol and context-level agreements
Bibliographic record
Abstract
Services and applications in pervasive environments must adapt to changes occurring in the surrounding environment and meet the needs of mobile users according to the users' changing situations. Existing context-aware architectures and middleware are faced with two problems. First, is their weakness in expressing complex inter-context relationships, stemming from use of less capable approaches to modeling contextual knowledge. Secondly, context dissemination methods used by these systems result in network flooding, unrestricted access to private context information, and the inability of consumers to limit or personalize received context. This thesis provides an ontology-based context-level negotiation protocol along with a context-aware system architecture. The protocol permits context consumers to personalize their received context information through negotiations with context providers. The thesis illustrates the use of this negotiation protocol through the design and implementation of a context-aware system architecture capable of acquiring, modeling, reasoning and disseminating context information through ontologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".