78 citations · 178 across the 14 of their papers we have counts for
14 papers
Adaptive Structural Similarity Preserving for Unsupervised Cross Modal Hashing
Liang Li, Baihua Zheng, Weiwei Sun
Cross-modal hashing is an important approach for multimodal data management and application. Existing unsupervised cross-modal hashing algorithms mainly rely on data features in pr…
Self-Guided Learning to Denoise for Robust Recommendation
Yunjun Gao, Yuntao Du, Yujia Hu +4
The ubiquity of implicit feedback makes them the default choice to build modern recommender systems. Generally speaking, observed interactions are considered as positive samples, w…
HAKG: Hierarchy-Aware Knowledge Gated Network for Recommendation
Yuntao Du, Xinjun Zhu, Lu Chen +2
Knowledge graph (KG) plays an increasingly important role to improve the recommendation performance and interpretability. A recent technical trend is to design end-to-end models ba…
CollaborER: A Self-supervised Entity Resolution Framework Using Multi-features Collaboration
Congcong Ge, Pengfei Wang, Lu Chen +3
Entity Resolution (ER) aims to identify whether two tuples refer to the same real-world entity and is well-known to be labor-intensive. It is a prerequisite to anomaly detection, a…
LargeEA: Aligning Entities for Large-scale Knowledge Graphs
Congcong Ge, Xiaoze Liu, Lu Chen +2
Entity alignment (EA) aims to find equivalent entities in different knowledge graphs (KGs). Current EA approaches suffer from scalability issues, limiting their usage in real-world…
Crowding Prediction of In-Situ Metro Passengers Using Smart Card Data
Xiancai Tian, Chen Zhang, Baihua Zheng
The metro system is playing an increasingly important role in the urban public transit network, transferring a massive human flow across space everyday in the city. In recent years…
Probabilistic Value Selection for Space Efficient Model
Gunarto Sindoro Njoo, Baihua Zheng, Kuo-Wei Hsu +1
An alternative to current mainstream preprocessing methods is proposed: Value Selection (VS). Unlike the existing methods such as feature selection that removes features and instan…
TRIPDECODER: Study Travel Time Attributes and Route Preferences of Metro Systems from Smart Card Data
Xiancai Tian, Baihua Zheng, Yazhe Wang +2
In this paper, we target at recovering the exact routes taken by commuters inside a metro system that arenot captured by an Automated Fare Collection (AFC) system and hence remain…
KGClean: An Embedding Powered Knowledge Graph Cleaning Framework
Congcong Ge, Yunjun Gao, Honghui Weng +3
The quality assurance of the knowledge graph is a prerequisite for various knowledge-driven applications. We propose KGClean, a novel cleaning framework powered by knowledge graph…
CrowdTSC: Crowd-based Neural Networks for Text Sentiment Classification
Keyu Yang, Yunjun Gao, Lei Liang +3
Sentiment classification is a fundamental task in content analysis. Although deep learning has demonstrated promising performance in text classification compared with shallow model…
Bus Frequency Optimization: When Waiting Time Matters in User Satisfaction
Songsong Mo, Zhifeng Bao, Baihua Zheng +1
Reorganizing bus frequency to cater for the actual travel demand can save the cost of the public transport system significantly. Many, if not all, existing studies formulate this a…
DeepDualMapper: A Gated Fusion Network for Automatic Map Extraction using Aerial Images and Trajectories
Hao Wu, Hanyuan Zhang, Xinyu Zhang +3
Automatic map extraction is of great importance to urban computing and location-based services. Aerial image and GPS trajectory data refer to two different data sources that could…
DeepTravel: a Neural Network Based Travel Time Estimation Model with Auxiliary Supervision
Hanyuan Zhang, Hao Wu, Weiwei Sun +1
Estimating the travel time of a path is of great importance to smart urban mobility. Existing approaches are either based on estimating the time cost of each road segment which are…
PRESS: A Novel Framework of Trajectory Compression in Road Networks
Renchu Song, Weiwei Sun, Baihua Zheng +1
Location data becomes more and more important. In this paper, we focus on the trajectory data, and propose a new framework, namely PRESS (Paralleled Road-Network-Based Trajectory C…