46 citations · 85 across the 10 of their papers we have counts for
7 papers · 1 filter
Sequential Recommendation for Cold-start Users with Meta Transitional Learning
Jianling Wang, Kaize Ding, James Caverlee
A fundamental challenge for sequential recommenders is to capture the sequential patterns of users toward modeling how users transit among items. In many practical scenarios, howev…
Fairness-aware Personalized Ranking Recommendation via Adversarial Learning
Ziwei Zhu, Jianling Wang, James Caverlee
Recommendation algorithms typically build models based on historical user-item interactions (e.g., clicks, likes, or ratings) to provide a personalized ranked list of items. These…
Understanding Car-Speak: Replacing Humans in Dealerships
Habeeb Hooshmand, James Caverlee
A large portion of the car-buying experience in the United States involves interactions at a car dealership. At the dealership, the car-buyer relays their needs to a sales represen…
Consistency-Aware Recommendation for User-Generated ItemList Continuation
Yun He, Yin Zhang, Weiwen Liu +1
User-generated item lists are popular on many platforms. Examples include video-based playlists on YouTube, image-based lists (or"boards") on Pinterest, book-based lists on Goodrea…
A Hierarchical Self-Attentive Model for Recommending User-Generated Item Lists
Yun He, Jianling Wang, Wei Niu +1
User-generated item lists are a popular feature of many different platforms. Examples include lists of books on Goodreads, playlists on Spotify and YouTube, collections of images o…
Pseudo-Implicit Feedback for Alleviating Data Sparsity in Top-K Recommendation
Yun He, Haochen Chen, Ziwei Zhu +1
We propose PsiRec, a novel user preference propagation recommender that incorporates pseudo-implicit feedback for enriching the original sparse implicit feedback dataset. Three of…