3 papers
cs.IR2023
A Self-Correcting Sequential Recommender
Yujie Lin, Chenyang Wang, Zhumin Chen +6
Sequential recommendations aim to capture users' preferences from their historical interactions so as to predict the next item that they will interact with. Sequential recommendati…
cs.CL2023
Graph2topic: an opensource topic modeling framework based on sentence embedding and community detection
Leihang Zhang, Jiapeng Liu, Qiang Yan
It has been reported that clustering-based topic models, which cluster high-quality sentence embeddings with an appropriate word selection method, can generate better topics than g…
cs.IR2023
Modeling Sequential Recommendation as Missing Information Imputation
Yujie Lin, Zhumin Chen, Zhaochun Ren +5
Side information is being used extensively to improve the effectiveness of sequential recommendation models. It is said to help capture the transition patterns among items. Most pr…