202 citations · 310 across the 24 of their papers we have counts for
5 papers · 1 filter
AE-smnsMLC: Multi-Label Classification with Semantic Matching and Negative Label Sampling for Product Attribute Value Extraction
Zhongfen Deng, Wei-Te Chen, Lei Chen +1
Product attribute value extraction plays an important role for many real-world applications in e-Commerce such as product search and recommendation. Previous methods treat it as a…
Multi-task Item-attribute Graph Pre-training for Strict Cold-start Item Recommendation
Yuwei Cao, Liangwei Yang, Chen Wang +4
Recommendation systems suffer in the strict cold-start (SCS) scenario, where the user-item interactions are entirely unavailable. The ID-based approaches completely fail to work. C…
Sequential Recommendation with Controllable Diversification: Representation Degeneration and Diversity
Ziwei Fan, Zhiwei Liu, Hao Peng +1
Sequential recommendation (SR) models the dynamic user preferences and generates the next-item prediction as the affinity between the sequence and items, in a joint latent space wi…
Zero-shot Item-based Recommendation via Multi-task Product Knowledge Graph Pre-Training
Ziwei Fan, Zhiwei Liu, Shelby Heinecke +4
Existing recommender systems face difficulties with zero-shot items, i.e. items that have no historical interactions with users during the training stage. Though recent works extra…
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders
Xiaohan Li, Zheng Liu, Luyi Ma +4
Recent studies on Next-basket Recommendation (NBR) have achieved much progress by leveraging Personalized Item Frequency (PIF) as one of the main features, which measures the frequ…