A Comparative User Study of Web Search Interfaces: HotMap, Concept Highlighter, and Google
Bibliographic record
Abstract
Users of traditional Web search engines commonly find it difficult to evaluate the results of their Web searches. We suggest the use of information visualization and interactive visual manipulation as methods for improving the ability of users to evaluate the results of a Web search. In this paper, we present the results of a user study that compared the search results interface provided by Google to that of two systems we have developed: HotMap and Concept Highlighter. We found that users were able to perform their searches faster with HotMap, were able to find more relevant documents with Concept Highlighter, and generally ranked these interfaces higher than Google with respect to subjective measures. When given a choice between these interfaces, participants ranked HotMap the highest, followed by Google and Concept Highlighter. These results indicate that even though the list-based representation of search results are common among search engines, visual and interactive interfaces to Web search results can be more efficient, effective, and satisfying to the users
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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 | 0.007 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".