192 citations · 378 across the 13 of their papers we have counts for
13 papers
Video and Audio are Images: A Cross-Modal Mixer for Original Data on Video-Audio Retrieval
Zichen Yuan, Qi Shen, Bingyi Zheng +3
Cross-modal retrieval has become popular in recent years, particularly with the rise of multimedia. Generally, the information from each modality exhibits distinct representations…
Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation
Yizhou Dang, Enneng Yang, Guibing Guo +5
Sequential recommendation is an important task to predict the next-item to access based on a sequence of interacted items. Most existing works learn user preference as the transiti…
AdaTask: A Task-aware Adaptive Learning Rate Approach to Multi-task Learning
Enneng Yang, Junwei Pan, Ximei Wang +6
Multi-task learning (MTL) models have demonstrated impressive results in computer vision, natural language processing, and recommender systems. Even though many approaches have bee…
Emotion-aware Chat Machine: Automatic Emotional Response Generation for Human-like Emotional Interaction
Wei Wei, Jiayi Liu, Xianling Mao +4
The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions. However, this challenge i…
NEUer at SemEval-2021 Task 4: Complete Summary Representation by Filling Answers into Question for Matching Reading Comprehension
Zhixiang Chen, Yikun Lei, Pai Liu +1
SemEval task 4 aims to find a proper option from multiple candidates to resolve the task of machine reading comprehension. Most existing approaches propose to concat question and o…
User-based Network Embedding for Collective Opinion Spammer Detection
Ziyang Wang, Wei Wei, Xian-Ling Mao +3
Due to the huge commercial interests behind online reviews, a tremendousamount of spammers manufacture spam reviews for product reputation manipulation. To further enhance the infl…
Target Guided Emotion Aware Chat Machine
Wei Wei, Jiayi Liu, Xianling Mao +5
The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions. However, this challenge i…
CmnRec: Sequential Recommendations with Chunk-accelerated Memory Network
Shilin Qu, Fajie Yuan, Guibing Guo +2
Recently, Memory-based Neural Recommenders (MNR) have demonstrated superior predictive accuracy in the task of sequential recommendations, particularly for modeling long-term item…
Generalized Embedding Machines for Recommender Systems
Enneng Yang, Xin Xin, Li Shen +1
Factorization machine (FM) is an effective model for feature-based recommendation which utilizes inner product to capture second-order feature interactions. However, one of the maj…
Research Commentary on Recommendations with Side Information: A Survey and Research Directions
Zhu Sun, Qing Guo, Jie Yang +4
Recommender systems have become an essential tool to help resolve the information overload problem in recent decades. Traditional recommender systems, however, suffer from data spa…
Future Data Helps Training: Modeling Future Contexts for Session-based Recommendation
Fajie Yuan, Xiangnan He, Haochuan Jiang +4
Session-based recommender systems have attracted much attention recently. To capture the sequential dependencies, existing methods resort either to data augmentation techniques or…
Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations
Hui Fang, Danning Zhang, Yiheng Shu +1
In the field of sequential recommendation, deep learning (DL)-based methods have received a lot of attention in the past few years and surpassed traditional models such as Markov c…
VSE-ens: Visual-Semantic Embeddings with Efficient Negative Sampling
Guibing Guo, Songlin Zhai, Fajie Yuan +2
Jointing visual-semantic embeddings (VSE) have become a research hotpot for the task of image annotation, which suffers from the issue of semantic gap, i.e., the gap between images…