Disentangling id and modality effects for session-based recommendation
Session-based recommendation aims to predict intents of anonymous users based on their
limited behaviors. Modeling user behaviors involves two distinct rationales: co-occurrence …
limited behaviors. Modeling user behaviors involves two distinct rationales: co-occurrence …
FineRec: Exploring Fine-grained Sequential Recommendation
Sequential recommendation is dedicated to offering items of interest for users based on their
history behaviors. The attribute-opinion pairs, expressed by users in their reviews for items …
history behaviors. The attribute-opinion pairs, expressed by users in their reviews for items …
Side Information-Driven Session-based Recommendation: A Survey
The session-based recommendation (SBR) garners increasing attention due to its ability to
predict anonymous user intents within limited interactions. Emerging efforts incorporate …
predict anonymous user intents within limited interactions. Emerging efforts incorporate …
Don't Click the Bait: Title Debiasing News Recommendation via Cross-Field Contrastive Learning
News recommendation emerges as a primary means for users to access content of interest
from the vast amount of news. The title clickbait extensively exists in news domain and …
from the vast amount of news. The title clickbait extensively exists in news domain and …
Integrating Multi-view Analysis: Multi-view Mixture-of-Expert for Textual Personality Detection
Textual personality detection aims to identify personality traits by analyzing user-generated
content. To achieve this effectively, it is essential to thoroughly examine user-generated …
content. To achieve this effectively, it is essential to thoroughly examine user-generated …