A Novel Approach for Frequent Phrase Mining in Web Search Engine Query Streams
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.
Bibliographic record
Abstract
In this paper, conceptual frequency rate, a new frequency definition suitable for query stream mining, is introduced. An online single-pass algorithm called OFSD (Online Frequent Sequence Discovery) is given, to mine the set of all conceptual frequent sequences in a data stream whose conceptual frequency rates satisfy a minimum user defined frequency rate. Phrase recommender algorithm is then described based on the set of conceptual frequent phrases extracted by the OFSD algorithm. We have also designed a query recommender algorithm, OQD (Online Query Discovery). OQD is used for comparison purposes along side the proposed phrase recommender algorithm. Simulation results show the efficiency of the proposed Phrase recommender algorithm compared to OQD.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 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