155 citations · 416 across the 26 of their papers we have counts for
26 papers
Multi-Dimensional Ability Diagnosis for Machine Learning Algorithms
Qi Liu, Zheng Gong, Zhenya Huang +5
Machine learning algorithms have become ubiquitous in a number of applications (e.g. image classification). However, due to the insufficient measurement of traditional metrics (e.g…
Generative Job Recommendations with Large Language Model
Zhi Zheng, Zhaopeng Qiu, Xiao Hu +3
The rapid development of online recruitment services has encouraged the utilization of recommender systems to streamline the job seeking process. Predominantly, current job recomme…
A Comprehensive Survey of Artificial Intelligence Techniques for Talent Analytics
Chuan Qin, Le Zhang, Yihang Cheng +8
In today's competitive and fast-evolving business environment, it is a critical time for organizations to rethink how to make talent-related decisions in a quantitative manner. Ind…
Multi-Temporal Relationship Inference in Urban Areas
Shuangli Li, Jingbo Zhou, Ji Liu +3
Finding multiple temporal relationships among locations can benefit a bunch of urban applications, such as dynamic offline advertising and smart public transport planning. While so…
Preference or Intent? Double Disentangled Collaborative Filtering
Chao Wang, Hengshu Zhu, Dazhong Shen +2
People usually have different intents for choosing items, while their preferences under the same intent may also different. In traditional collaborative filtering approaches, both…
A Survey on Large Language Models for Recommendation
Likang Wu, Zhi Zheng, Zhaopeng Qiu +9
Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recomm…
Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph
Chenguang Du, Kaichun Yao, Hengshu Zhu +3
Recent years have witnessed the rapid development of heterogeneous graph neural networks (HGNNs) in information retrieval (IR) applications. Many existing HGNNs design a variety of…
Towards Table-to-Text Generation with Pretrained Language Model: A Table Structure Understanding and Text Deliberating Approach
Miao Chen, Xinjiang Lu, Tong Xu +4
Although remarkable progress on the neural table-to-text methods has been made, the generalization issues hinder the applicability of these models due to the limited source tables.…
A Contextual Master-Slave Framework on Urban Region Graph for Urban Village Detection
Congxi Xiao, Jingbo Zhou, Jizhou Huang +4
Urban villages (UVs) refer to the underdeveloped informal settlement falling behind the rapid urbanization in a city. Since there are high levels of social inequality and social ri…
Modelling of Bi-directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-in Identification
Dongbo Xi, Fuzhen Zhuang, Yanchi Liu +3
Human mobility data accumulated from Point-of-Interest (POI) check-ins provides great opportunity for user behavior understanding. However, data quality issues (e.g., geolocation i…
Towards Robust Knowledge Graph Embedding via Multi-task Reinforcement Learning
Zhao Zhang, Fuzhen Zhuang, Hengshu Zhu +4
Nowadays, Knowledge graphs (KGs) have been playing a pivotal role in AI-related applications. Despite the large sizes, existing KGs are far from complete and comprehensive. In orde…
Exploiting Cross-Modal Prediction and Relation Consistency for Semi-Supervised Image Captioning
Yang Yang, Hongchen Wei, Hengshu Zhu +3
The task of image captioning aims to generate captions directly from images via the automatically learned cross-modal generator. To build a well-performing generator, existing appr…
Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness
Dazhong Shen, Chuan Qin, Chao Wang +3
As one of the most popular generative models, Variational Autoencoder (VAE) approximates the posterior of latent variables based on amortized variational inference. However, when t…
Adversarial Neural Trip Recommendation
Linlang Jiang, Jingbo Zhou, Tong Xu +4
Trip recommender system, which targets at recommending a trip consisting of several ordered Points of Interest (POIs), has long been treated as an important application for many lo…
GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction
Shuangli Li, Jingbo Zhou, Tong Xu +2
Recently many efforts have been devoted to applying graph neural networks (GNNs) to molecular property prediction which is a fundamental task for computational drug and material di…
MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal
Weijia Zhang, Hao Liu, Lijun Zha +4
Real estate appraisal refers to the process of developing an unbiased opinion for real property's market value, which plays a vital role in decision-making for various players in t…
Butterfly-Core Community Search over Labeled Graphs
Zheng Dong, Xin Huang, Guorui Yuan +2
Community search aims at finding densely connected subgraphs for query vertices in a graph. While this task has been studied widely in the literature, most of the existing works on…
A Survey on Knowledge Graph-Based Recommender Systems
Qingyu Guo, Fuzhen Zhuang, Chuan Qin +4
To solve the information explosion problem and enhance user experience in various online applications, recommender systems have been developed to model users preferences. Although…
SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback
Chao Wang, Hengshu Zhu, Chen Zhu +2
The recent development of online recommender systems has a focus on collaborative ranking from implicit feedback, such as user clicks and purchases. Different from explicit ratings…
A Machine Learning-enhanced Robust P-Phase Picker for Real-time Seismic Monitoring
Dazhong Shen, Qi Zhang, Tong Xu +7
Identifying the arrival times of seismic P-phases plays a significant role in real-time seismic monitoring, which provides critical guidance for emergency response activities. Whil…
STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control
Yanan Wang, Tong Xu, Xin Niu +3
The development of intelligent traffic light control systems is essential for smart transportation management. While some efforts have been made to optimize the use of individual t…
Enhancing Person-Job Fit for Talent Recruitment: An Ability-aware Neural Network Approach
Chuan Qin, Hengshu Zhu, Tong Xu +4
The wide spread use of online recruitment services has led to information explosion in the job market. As a result, the recruiters have to seek the intelligent ways for Person Job…
Person-Job Fit: Adapting the Right Talent for the Right Job with Joint Representation Learning
Chen Zhu, Hengshu Zhu, Hui Xiong +4
Person-Job Fit is the process of matching the right talent for the right job by identifying talent competencies that are required for the job. While many qualitative efforts have b…
Recruitment Market Trend Analysis with Sequential Latent Variable Models
Chen Zhu, Hengshu Zhu, Hui Xiong +2
Recruitment market analysis provides valuable understanding of industry-specific economic growth and plays an important role for both employers and job seekers. With the rapid deve…