Service Package Recommendation for Mashup Development Based on a Multi-level Relational Network. - Jian Cao 001; Yijing Lu; Nengjun Zhu (ICSOC, 2016)

GTRM: A Top-N Recommendation Model for Smartphone Applications. - Nengjun Zhu; Jian Cao 001 (ICWS, 2017)

An Adaptive k-NN Classifier for Medical Treatment Recommendation Under Concept Drift. - Nengjun Zhu; Jian Cao 001; Yan Zhang (ChineseCSCW, 2018)

CPL: A Combined Framework of Pointwise Prediction and Learning to Rank for top-N Recommendations with Implicit Feedback. - Nengjun Zhu; Jian Cao 001 (WISE, 2019)

Enhancing Cross-domain Recommendation through Preference Structure Information Sharing. - Nengjun Zhu; Jian Cao 001 (ICWS, 2020)

Spatio-Temporal Dual Graph Attention Network for Query-POI Matching. - Zixuan Yuan; Hao Liu 026; Yanchi Liu; Denghui Zhang; Fei Yi; Nengjun Zhu; Hui Xiong 001 (SIGIR, 2020)

Sequential Modeling of Hierarchical User Intention and Preference for Next-item Recommendation. - Nengjun Zhu; Jian Cao 001; Yanchi Liu; Yang Yang 074; Haochao Ying; Hui Xiong 001 (WSDM, 2020)

A semi-supervised attention model for identifying authentic sneakers. - Yang Yang 074; Nengjun Zhu; Yi-Feng Wu; Jian Cao 001; De-Chuan Zhan; Hui Xiong 001 (Big Data Min. Anal., 2020)

A Decision Support System with Intelligent Recommendation for Multi-disciplinary Medical Treatment. - Nengjun Zhu; Jian Cao 001; Kunwei Shen; Xiaosong Chen; Siji Zhu (ACM Trans. Multim. Comput. Commun. Appl., 2020)

A New $k$-Nearest Neighbors Algorithm for Learning from Multiple Experts' Uncertain Decisions. - Zhengfei Shen; Jian Cao 001; Nengjun Zhu; Xiaosong Chen (CSCWD, 2021)

Leveraging pointwise prediction with learning to rank for top-N recommendation. - Nengjun Zhu; Jian Cao 001; Xinjiang Lu; Qi Gu (World Wide Web, 2021)

Learning User Embeddings Based on Long Short-Term User Group Modeling for Next-Item Recommendation. - Nengjun Zhu; Jieyun Huang; Jian Cao 001; Shanshan Feng (ChineseCSCW (2), 2022)

CAPTOR: A Crowd-Aware Pre-Travel Recommender System for Out-of-Town Users. - Haoran Xin 001; Xinjiang Lu; Nengjun Zhu; Tong Xu 001; Dejing Dou; Hui Xiong 001 (SIGIR, 2022)

Multi-label disaster text classification via supervised contrastive learning for social media data. - Shaorong Xie; Chunning Hou; Hang Yu 006; Zhenyu Zhang 013; Xiangfeng Luo; Nengjun Zhu (Comput. Electr. Eng., 2022)

RecNet: A Resource-Constraint Aware Neural Network for Used Car Recommendation. - Haihua Shi; Jianjun Qian; Nengjun Zhu; Tong Zhang 021; Zhen Cui 001; Qianliang Wu; Shanshan Feng (Int. J. Comput. Intell. Syst., 2022)

Causality-aware Enhanced Model for Multi-hop Question Answering over Knowledge Graphs. - Yuan Sui; Shanshan Feng; Huaxiang Zhang 001; Jian Cao 001; Liang Hu 004; Nengjun Zhu (Knowl. Based Syst., 2022)

Predicting a Person's Next Activity Region with a Dynamic Region-Relation-Aware Graph Neural Network. - Nengjun Zhu; Jian Cao 001; Xinjiang Lu; Chuanren Liu; Hao Liu 026; Yanyan Li; Xiangfeng Luo; Hui Xiong 001 (ACM Trans. Knowl. Discov. Data, 2022)

Learning a Hierarchical Intent Model for Next-Item Recommendation. - Nengjun Zhu; Jian Cao 001; Xinjiang Lu; Hui Xiong 001 (ACM Trans. Inf. Syst., 2022)

SNN-BS: A Clinical Terminology Standardization Method Using Siamese Networks with Batch Sampling Strategy. - Xiao Wei; Xiaoxin Wang; Nengjun Zhu (ADMA (2), 2023)

FRS4CPP: A Fair Recommendation Strategy Considering Interests of Users, Providers and Platform. - Haiyan Zhao 002; Ping Zhou; Jian Cao 001; Nengjun Zhu (ChineseCSCW (1), 2023)

MtiRec: A Medical Test Recommender System based on the Analysis of Treatment Programs. - Nengjun Zhu; Jieyun Huang; Jian Cao 001; Xinjiang Lu; Hao Liu 026; Hui Xiong 001 (ICDM, 2023)

SMONE: A Session-based Recommendation Model Based on Neighbor Sessions with Similar Probabilistic Intentions. - Bohan Jia; Jian Cao 001; Shiyou Qian; Nengjun Zhu; Xin Dong 012; Liang Zhang; Lei Cheng 005; Linjian Mo (ACM Trans. Knowl. Discov. Data, 2023)

Enhancing Next-Item Recommendation Through Adaptive User Group Modeling. - Nengjun Zhu; Lingdan Sun; Jian Cao 001; Xinjiang Lu; Runtong Li (J. Soc. Comput., 2023)

Early Fire Detection Based on Local Morphological Knowledge Matching. - Xinzhi Wang 001; Mengyue Li; Nengjun Zhu; Jiayan Qian; Zhanyi Zheng (ICDM, 2024)

Exploitation or Exploration Next? User Behavior Decoupling and Emerging Intent Modeling for Next-Item Recommendation. - Nengjun Zhu; Lingdan Sun; Xiangfeng Luo; Jian Cao 001; Qi Zhang 020; Xinjiang Lu (ICDM, 2024)

ProSwats: A Proxy-based Scientific Workflow Retrieval Approach by Bridging the Gap between Textual and Structural Semantics. - Yang Gu 002; Jian Cao 001; Shiyou Qian; Nengjun Zhu; Wei Guan 006 (ICWS, 2024)

R2V-MIF: Rule-to-Vector Contrastive Learning and Multi-channel Information Fusion for Therapy Recommendation. - Nengjun Zhu; Jieyun Huang; Jian Cao 001; Liang Hu 004; Zixuan Yuan; Huanjing Gao (IJCAI, 2024)

VR-DiagNet: Medical Volumetric and Radiomic Diagnosis Networks with Interpretable Clinician-like Optimizing Visual Inspection. - Shouyu Chen; Liang Hu 004; Tangwei Ye; Zhongyuan Lai; Qi Zhang 020; Ke Liu; Usman Naseem; Ke Sun; Nengjun Zhu (ACM Multimedia, 2024)

MANSOR: A module alignment method based on neighbor information for scientific workflow. - Yang Gu 002; Jian Cao 001; Shiyou Qian; Nengjun Zhu; Wei Guan 006 (Concurr. Comput. Pract. Exp., 2024)

Towards Human-Like Machine Comprehension: Few-Shot Relational Learning in Visually-Rich Documents. - Hao Wang 097; Tang Li; Chenhui Chu; Nengjun Zhu; Rui Wang 015; Pinpin Zhu (CoRR, 2024)

Entity recognition based on heterogeneous graph reasoning of visual region and text candidate. - Xinzhi Wang 001; Nengjun Zhu; Jiahao Li; Yudong Chang; Zhennan Li (Mach. Learn., 2024)

IN-GFD: An Interpretable Graph Fraud Detection Model for Spam Reviews. - Hang Yu 006; Weixu Liu; Nengjun Zhu; Pengbo Li; Xiangfeng Luo (IEEE Trans. Artif. Intell., 2024)

LEVER: Online Adaptive Sequence Learning Framework for High-Frequency Trading. - Zixuan Yuan; Junming Liu; Haoyi Zhou; Denghui Zhang; Hao Liu 026; Nengjun Zhu; Hui Xiong 001 (IEEE Trans. Knowl. Data Eng., 2024)

Promoting Knowledge Base Question Answering by Directing LLMs to Generate Task-relevant Logical Forms. - Jianqi Gao 001; Jian Cao 001; Ranran Bu; Nengjun Zhu; Wei Guan 006; Hang Yu 006 (AAAI, 2025)

ADELA: Accelerating Evolutionary Design of Machine Learning Pipelines with the Accompanying Surrogate Model. - Yang Gu 002; Jian Cao 001; Hengyu You; Nengjun Zhu; Shiyou Qian (AAAI, 2025)

MMGCL: Multi-scale and multi-channel graph contrastive learning for flight anomaly detection. - Nengjun Zhu; Yuqiang Ren; Yu Liu; Hang Yu 006; Xinzhi Wang 001; Xiangfeng Luo (Knowl. Based Syst., 2025)

Distributed Recommendation Systems: Survey and Research Directions. - Qiqi Cai; Jian Cao 001; Guandong Xu; Nengjun Zhu (ACM Trans. Inf. Syst., 2025)

Unsupervised Graph Anomaly Detection via Multi-Hypersphere Heterophilic Graph Learning. - Hang Ni; Jindong Han; Nengjun Zhu; Hao Liu 026 (CoRR, 2025)