Name
Abstract | ||
|---|---|---|
Diversity has been taken into consideration by existing Web image search engines in ranking search results. However, there is no thorough investigation of how diversity affects user satisfaction in image search. In this article, we address the following questions: (1) How do different factors, such as content and visual presentations, affect users’ perception of diversity? (2) How does search result diversity affect user satisfaction with different search intents? To answer those questions, we conduct a set of laboratory user studies to collect users’ perceived diversity annotations and search satisfaction. We find that the existence of nearly duplicated image results has the largest impact on users’ perceived diversity, followed by the similarity in content and visual presentations. Besides these findings, we also investigate the relationship between diversity and satisfaction in image search. Specifically, we find that users’ preference for diversity varies across different search intents. When users want to collect information or save images for further usage (the Locate search tasks), more diversified result lists lead to higher satisfaction levels. The insights may help commercial image search engines to design better result ranking strategies and evaluation metrics.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3320118 | ACM Transactions on Information Systems (TOIS) |
Keywords | Field | DocType |
Image search, image diversity, user satisfaction | Search engine,Ranking,Information retrieval,Computer science,User studies,Perception,Web image | Journal |
Volume | Issue | ISSN |
37 | 3 | 1046-8188 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhijing Wu | 1 | 25 | 4.15 |
| Ke Zhou | 2 | 790 | 40.82 |
| Yiqun Liu | 3 | 1592 | 136.51 |
| Min Zhang | 4 | 1658 | 134.93 |
| Shaoping Ma | 5 | 1544 | 126.00 |