Multiple Materialized View Selection for XPath Query Rewriting
Why this work is in the frame
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Bibliographic record
Abstract
We study the problem of answering XPATH queries using multiple materialized views. Despite the efforts on answering queries using single materialized view, answering queries using multiple views remains relatively new. We address two important aspects of this problem: multiple-view selection and equivalent multiple-view rewriting. With regards to the first problem, we propose an NFA-based approach (called VFILTER) to filter views that cannot be used to answer a given query. We then present the criterion for multiple view/query answerability. Based on the output of VFILTER, we further propose a heuristic method to identify a minimal view set that can answer a given query. For the problem of multiple-view rewriting, we first refine the materialized fragments of each selected view (like pushing selection), we then join the refined fragments utilizing an encoding scheme. Finally, we extract the result of the query from the materialized fragments of a single view. Experiments show the efficiency of our approach.
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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 it