foreign
发表于 2025-3-28 16:45:25
EPARS: Early Prediction of At-Risk Students with Online and Offline Learning Behaviorsks mostly rely on either online or offline learning behaviors which are not comprehensive enough to capture the whole learning processes and lead to unsatisfying prediction performance. We propose a novel algorithm (EPARS) that could early predict STAR in a semester by modeling online and offline le
传授知识
发表于 2025-3-28 21:25:41
MRMRP: Multi-source Review-Based Model for Rating Predictionfew years, many studies in recommender systems take user reviews into consideration and achieve promising performance. However, in daily life, most consumers are used to leaving no comments for products purchased and most reviews written by consumers are short, which leads to the performance degrada
CORD
发表于 2025-3-28 23:52:28
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Debark
发表于 2025-3-29 06:06:40
Few-Shot Human Activity Recognition on Noisy Wearable Sensor Datanew-class activities unseen during training from a few samples. Very few researches of few-shot learning (FSL) have been done in HAR to address the above problem, though FSL has been widely used in computer vision tasks. Besides, it is impractical to annotate sensor data with accurate activity label
绿州
发表于 2025-3-29 09:00:23
Adversarial Generation of Target Review for Rating Predictionisting methods learn the latent representations from the user’s and the item’s historical reviews, and then combine these two representations for rating prediction. The fatal limitation in these methods is that they are unable to utilize the most predictive review of the target user for the target i
微粒
发表于 2025-3-29 14:43:07
Hybrid Attention Based Neural Architecture for Text Semantics Similarity Measurementguage processing. It is a complicated task due to the ambiguity and variability of linguistic expression. Previous studies focus on modeling the representation of a sentence in multiple granularities and then measure the similarity based on the representations. However, above methods cannot make ful
卡死偷电
发表于 2025-3-29 16:12:43
Instance Explainable Multi-instance Learning for ROI of Various Dataion can be generalized to the bag containing multiple data instances, i.e., identify the instances that probably arouse our interest. Under the circumstance without instance labels, generalized ROI estimation problem can be addressed in the framework of Multi-Instance Learning (MIL). MIL is a variat
BRAWL
发表于 2025-3-29 23:14:57
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无王时期,
发表于 2025-3-30 00:26:20
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pulmonary-edema
发表于 2025-3-30 06:56:06
Progressive Term Frequency Analysis on Large Text Collectionsep up with the growth of data. The delays when processing huge textual data can negatively impact user activity and insight. This calls for a paradigm shift from blocking fashion to progressive processing. In this paper, we propose a sample-based progressive processing model that focuses on term fre