Pinterest Board Recommendation for Twitter Users
September 01, 2015 Β· Declared Dead Β· π ACM Multimedia
"No code URL or promise found in abstract"
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Authors
Xitong Yang, Yuncheng Li, Jiebo Luo
arXiv ID
1509.00511
Category
cs.SI: Social & Info Networks
Cross-listed
cs.MM
Citations
32
Venue
ACM Multimedia
Last Checked
3 months ago
Abstract
Pinboard on Pinterest is an emerging media to engage online social media users, on which users post online images for specific topics. Regardless of its significance, there is little previous work specifically to facilitate information discovery based on pinboards. This paper proposes a novel pinboard recommendation system for Twitter users. In order to associate contents from the two social media platforms, we propose to use MultiLabel classification to map Twitter user followees to pinboard topics and visual diversification to recommend pinboards given user interested topics. A preliminary experiment on a dataset with 2000 users validated our proposed system.
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