Ausgabe 2/2023
Special Issue: Data science for next-generation recommender systems
Inhalt (11 Artikel)
Data science for next-generation recommender systems
Shoujin Wang, Yan Wang, Fikret Sivrikaya, Sahin Albayrak, Vito Walter Anelli
TPEDTR: temporal preference embedding-based deep tourism recommendation with card transaction data
Minsung Hong, Namho Chung, Chulmo Koo, Sun-Young Koh
Combination of individual and group patterns for time-sensitive purchase recommendation
Anton Lysenko, Egor Shikov, Klavdiya Bochenina
When algorithm selection meets Bi-linear Learning to Rank: accuracy and inference time trade off with candidates expansion
Jing Yuan, Christian Geissler, Weijia Shao, Andreas Lommatzsch, Brijnesh Jain
Modeling uncertainty to improve personalized recommendations via Bayesian deep learning
Xin Wang, Serdar Kadıoğlu
ScholarRec: a scholars’ recommender system that combines scholastic influence and social collaborations in academic social networks
Mitali Desai, Rupa G. Mehta, Dipti P. Rana
A probabilistic perspective on nearest neighbor for implicit recommendation
Domokos M. Kelen, Andras A. Benczúr
Privacy preserving cold-start recommendation for out-of-matrix users via content baskets
Michael Sun, Andrew Wang
Pull–push: a measure of over- or underpersonalization in recommendation
Gebrekirstos G. Gebremeskel, Arjen P. de Vries
Attenuated sentiment-aware sequential recommendation
Donglin Zhou, Zhihong Zhang, Yangxin Zheng, Zhenting Zou, Lin Zheng
A deep meta-level spatio-categorical POI recommender system
Chaima Laroussi, Raouia Ayachi