Topic familiarity and its effects on term selection and browsing in a thesaurus‐enhanced search environment
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
Purpose To evaluate the extent to which familiarity with search topics affects the ways in which users select and browse search terms in a thesaurus‐enhanced search setting. Design/methodology/approach An experimental methodology was adopted to study users’ search behaviour in an operational information retrieval environment. Findings Topic familiarity and subject knowledge influence some search and interaction behaviours. Searches involving moderately and very familiar topics were associated with browsing around twice as many thesaurus terms as was the case for unfamiliar topics. Research limitations/implications Some search behaviours such as thesaurus browsing and term selection could be used as an indication of user levels of topic familiarity. Practical implications The results of this study provide design implications as to how to develop personalized search interfaces where users with varying levels of familiarity with search topics can carry out searches. Originality/value This paper establishes the importance of topic familiarity characteristics and the effects of those characteristics on users’ interaction with search interfaces enhanced with semantic tools such as thesauri.
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 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