Zi Huang

Enhancing Collaborative Filtering with Generative Augmentation

2019

Collaborative filtering (CF) has become one of the most popular and widely used methods in recommender systems, but its performance degrades sharply for users with rare interaction data. Most existing hybrid CF methods try to …

Interpretable Signed Link Prediction With Signed Infomax Hyperbolic Graph

2021 · IEEE Transactions on Knowledge and Data Engineering

Signed link prediction in social networks aims to reveal the underlying relationships (i.e., links) among users (i.e., nodes) given their existing positive and negative interactions observed. Most of the prior efforts are devoted to learning …

Privacy Protection in Deep Multi-modal Retrieval

2021

Deep learning techniques have ushered in significant progress in large-scale multi-modal retrieval. Nevertheless, the advanced techniques may be used nefariously to conduct a search that violates the privacy of individuals. In this paper, we propose …

Graph Embedding for Recommendation against Attribute Inference Attacks

2021

In recent years, recommender systems play a pivotal role in helping users identify the most suitable items that satisfy personal preferences. As user-item interactions can be naturally modelled as graph-structured data, variants of graph convolutional …

Long short-term enhanced memory for sequential recommendation

2022 · World Wide Web

Abstract Sequential recommendation is a stream of studies on recommender systems, which focuses on predicting the next item a user interacts with by modeling the dynamic sequence of user-item interactions. Since being born to explore …

GSMFlow: Generation Shifts Mitigating Flow for Generalized Zero-Shot Learning

2022 · IEEE Transactions on Multimedia

Generalized Zero-Shot Learning (GZSL) aims to recognize images not only for seen classes but also for unseen ones by transferring semantic-visual relationships from the seen to the unseen classes. It is an intuitive solution to …

AgenticScholar: Agentic Data Management with Pipeline Orchestration for Scholarly Corpora

2026 · Proceedings of the ACM on Management of Data

Managing the rapidly growing scholarly corpus poses significant challenges in representation, reasoning, and efficient analysis. An ideal system should unify structured knowledge management, agentic planning, and interpretable execution to support diverse scholarly queries – from …

Joint Modeling of User Check-in Behaviors for Real-time Point-of-Interest Recommendation

2016 · ACM Transactions on Information Systems

Point-of-Interest (POI) recommendation has become an important means to help people discover attractive and interesting places, especially when users travel out of town. However, the extreme sparsity of a user-POI matrix creates a severe challenge. …

Joint Event-Partner Recommendation in Event-Based Social Networks

2018

With the prevalent trend of combining online and offline interactions among users in event-based social networks (EBSNs), event recommendation has become an essential means to help people discover new interesting events to attend. However, existing …

Streaming Ranking Based Recommender Systems

2018

Studying recommender systems under streaming scenarios has become increasingly important because real-world applications produce data continuously and rapidly. However, most existing recommender systems today are designed in the context of an offline setting. Compared with …

Neural Memory Streaming Recommender Networks with Adversarial Training

2018

With the increasing popularity of various social media and E-commerce platforms, large volumes of user behaviour data (e.g., user transaction data, rating and review data) are being continually generated at unprecedented and ever-increasing scales. It …

Enhancing Social Recommendation With Adversarial Graph Convolutional Networks

2020 · IEEE Transactions on Knowledge and Data Engineering

Social recommender systems are expected to improve recommendation quality by incorporating social information when there is little user-item interaction data. However, recent reports from industry show that social recommender systems consistently fail in practice. According …

Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation

2022 · Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining

Recent advancements of sequential deep learning models such as Transformer and BERT have significantly facilitated the sequential recommendation. However, according to our study, the distribution of item embeddings generated by these models tends to degenerate …