WebKDD 2005
Bibliographic record
Abstract
In this report, we summarize the contents and outcomes of the recent WebKDD 2005 workshop on Web Mining and Web Usage Analysis that was held in conjunction with the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2005), August 21-24, 2005, in Chicago, Illinois. The theme of this workshop was "Taming Evolving, Expanding and Multi-faceted Web Clickstreams". We also reflect on possible new directions in Web mining research as reflected by the discussions and the talks during the workshop.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.030 | 0.058 |
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 source (direct Gemma or distilled Codex), 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".