Name
Abstract | ||
|---|---|---|
Recommender systems are commonly used in entertainment, news, e-commerce, and social media. Document recommendation is a new and under-explored application area, in which both re-finding and discovery of documents need to be supported. In this paper we provide an initial exploration of users' experience with recommended documents, with a focus on how prior interactions influence recognition and interest. Through a field study of more than 100 users, we investigate the effects of past interactions with recommended documents on users' recognition of, prior intent to open, and interest in the documents. We examined different presentations of interaction history, and the recency and richness of prior interaction. We found that presentation only influenced recognition time. Our findings also indicate that people are more likely to recognize documents they had accessed recently and to do so more quickly. Similarly, documents that people had interacted with more deeply were also more frequently and quickly recognized. However, people were more interested in older documents or those with which they had less involved interactions. This finding suggests that in addition to helping users quickly access documents they intend to re-find, document recommendation can add value in helping users discover other documents. Our results offer implications for designing document recommendation systems that help users fulfil different needs.
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Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3343413.3377977 | CHIIR '20: Conference on Human Information Interaction and Retrieval
Vancouver BC
Canada
March, 2020 |
Keywords | DocType | ISBN |
Document Recommendation, User Behavior, Presentation of Recommended Items, User-Document Interactions, Document Re-finding, Document Discovery | Conference | 978-1-4503-6892-6 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Farnaz Jahanbakhsh | 1 | 3 | 0.71 |
| Ahmed Hassan | 2 | 943 | 57.64 |
| Susan Dumais | 3 | 13948 | 2130.47 |
| Xuhai Xu | 4 | 1 | 0.69 |