2 citations · 2 across the 5 of their papers we have counts for
5 papers
Organized Event Participant Prediction Enhanced by Social Media Retweeting Data
Yihong Zhang, Takahiro Hara
Nowadays, many platforms on the Web offer organized events, allowing users to be organizers or participants. For such platforms, it is beneficial to predict potential event partici…
Causal Disentangled Variational Auto-Encoder for Preference Understanding in Recommendation
Siyu Wang, Xiaocong Chen, Quan Z. Sheng +2
Recommendation models are typically trained on observational user interaction data, but the interactions between latent factors in users' decision-making processes lead to complex…
Debiasing Graph Transfer Learning via Item Semantic Clustering for Cross-Domain Recommendations
Zhi Li, Daichi Amagata, Yihong Zhang +4
Deep learning-based recommender systems may lead to over-fitting when lacking training interaction data. This over-fitting significantly degrades recommendation performances. To ad…
Using Social Media Background to Improve Cold-start Recommendation Deep Models
Yihong Zhang, Takuya Maekawa, Takahiro Hara
In recommender systems, a cold-start problem occurs when there is no past interaction record associated with the user or item. Typical solutions to the cold-start problem make use…
A General Method for Event Detection on Social Media
Yihong Zhang, Masumi Shirakawa, Takahiro Hara
Event detection on social media has attracted a number of researches, given the recent availability of large volumes of social media discussions. Previous works on social media eve…