Law article-enhanced legal case matching: A causal learning approach

Z Sun, J Xu, X Zhang, Z Dong, JR Wen - Proceedings of the 46th …, 2023 - dl.acm.org
Legal case matching, which automatically constructs a model to estimate the similarities
between the source and target cases, has played an essential role in intelligent legal …

Dynamic Hierarchical Attention Network for news recommendation

Q Zhao, X Chen, H Zhang, X Li - Expert Systems with Applications, 2024 - Elsevier
Existing news recommendation methods often rely on static user–news interactions that fail
to account for the evolving nature of users' preferences over time. To address the prevalent …

Mitigating Dual Latent Confounding Biases in Recommender Systems

J Deng, Q Chen, D Cheng, J Li, L Liu, X Du - arxiv preprint arxiv …, 2024 - arxiv.org
Recommender systems are extensively utilised across various areas to predict user
preferences for personalised experiences and enhanced user engagement and satisfaction …

UniSAR: Modeling User Transition Behaviors between Search and Recommendation

T Shi, Z Si, J Xu, X Zhang, X Zang, K Zheng… - Proceedings of the 47th …, 2024 - dl.acm.org
Nowadays, many platforms provide users with both search and recommendation services as
important tools for accessing information. The phenomenon has led to a correlation between …

To Search or to Recommend: Predicting Open-App Motivation with Neural Hawkes Process

Z Sun, Z Si, X Zhang, X Zang, Y Song, H Xu… - Proceedings of the 47th …, 2024 - dl.acm.org
Incorporating Search and Recommendation (S&R) services within a singular application is
prevalent in online platforms, leading to a new task termed open-app motivation prediction …

Enhancing Click-through Rate Prediction in Recommendation Domain with Search Query Representation

Y Wang, M Chen, Y Hu, W Guo, Y Zhang… - Proceedings of the 33rd …, 2024 - dl.acm.org
Many platforms, such as e-commerce websites, offer both search and recommendation
services simultaneously to better meet users' diverse needs. Recommendation services …

Counterfactual Learning-Driven Representation Disentanglement for Search-Enhanced Recommendation

J Cui, X Chen, S **ao, C Ju, J Lan, Q Liu… - arxiv preprint arxiv …, 2024 - arxiv.org
For recommender systems in internet platforms, search activities provide additional insights
into user interest through query-click interactions with items, and are thus widely used for …

Multi-Cause Deconfounding for Recommender Systems with Latent Confounders

Z Huang, S Zhang, D Cheng, J Li, L Liu… - arxiv preprint arxiv …, 2024 - arxiv.org
In recommender systems, various latent confounding factors (eg, user social environment
and item public attractiveness) can affect user behavior, item exposure, and feedback in …