Hybrid data combining both tabular and textual content (eg, financial reports) are quite pervasive in the real world. However, Question Answering (QA) over such hybrid data is …
Recommender systems usually amplify the biases in the data. The model learned from historical interactions with imbalanced item distribution will amplify the imbalance by over …
Short text classification has been widely explored in news tagging to provide more efficient search strategies and more effective search results for information retrieval. However, most …
L Li, P Wang, X Zheng, Q Xie, X Tao, JD Velásquez - Information Fusion, 2023 - Elsevier
Automatic tagging on software information sites is a tag recommendation service. It aims to recommend content-based tags for a software object to help developers make distinctions …
The integration of deep learning (DL) and fuzzy learning (FL) is considered a recently emerging and promising research direction in data embedding. The integrated fuzzy neural …
Existing methods towards outfit compatibility modeling seldom explicitly consider multimodal correlations. In this work, we explore the consistent and complementary correlations for …
Multi-label datasets often contain label information with missing values and recovering them is a non-trivial challenge. Several methods augment the observed label matrix by …
Y Hu, L Nie, M Liu, K Wang, Y Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Video moment localization, as an important branch of video content analysis, has attracted extensive attention in recent years. However, it is still in its infancy due to the following …
Traditional recommenders suffer from hidden confounding factors, leading to the spurious correlations between user/item profiles and user preference prediction, ie, the confounding …