Enterprise Isomorphic Mapping Mechanism: Towards Ontology Interoperability in EIS Development. - Mingxin Gan (ICEBE, 2009)

DOPCA: A New Method for Calculating Ontology-Based Semantic Similarity. - Mingxin Gan; Xue Dou; Daoping Wang; Rui Jiang 001 (ACIS-ICIS, 2011)

A genetic algorithm for optimizing subnetwork markers for the study of breast cancer metastasis. - Jiaxin Wu 005; Mingxin Gan; Rui Jiang 001 (ICNC, 2011)

Constructing a gene semantic similarity network for the inference of disease genes. - Rui Jiang 001; Mingxin Gan; Peng He (BMC Syst. Biol., 2011)

Prioritisation of candidate Single Amino Acid Polymorphisms using one-class learning machines. - Jiaxin Wu 005; Mingxin Gan; Rui Jiang 001 (Int. J. Comput. Biol. Drug Des., 2011)

Improving Recommendation Performance through Ontology-Based Semantic Similarity. - Mingxin Gan; Xue Dou; Rui Jiang 001 (ICICA (LNCS), 2012)

Ontology-Based Genes Similarity Calculation with TF-IDF. - Yue Huang; Mingxin Gan; Rui Jiang 001 (ICICA (LNCS), 2012)

Identification of disease-related nsSNPs via the integration of protein sequence features and domain-domain interaction data. - Rui Jiang 001; Mingxin Gan; Jiaxin Wu 005 (Int. J. Comput. Biol. Drug Des., 2012)

Inferring semantic similarity through correlating information contents of gene ontology terms. - Mingxin Gan; Rui Jiang 001 (BIBM, 2013)

Improving accuracy and diversity of personalized recommendation through power law adjustments of user similarities. - Mingxin Gan; Rui Jiang 001 (Decis. Support Syst., 2013)

Constructing a user similarity network to remove adverse influence of popular objects for personalized recommendation. - Mingxin Gan; Rui Jiang 001 (Expert Syst. Appl., 2013)

Correlating Information Contents of Gene Ontology Terms to Infer Semantic Similarity of Gene Products. - Mingxin Gan (Comput. Math. Methods Medicine, 2014)

ROUND: Walking on an object-user heterogeneous network for personalized recommendations. - Mingxin Gan; Rui Jiang 001 (Expert Syst. Appl., 2015)

Motif-Plus: incorporation of network motifs into top-n friendship recommendations. - Mingxin Gan; Le Li (Int. J. Reason. based Intell. Syst., 2015)

COUSIN: A network-based regression model for personalized recommendations. - Mingxin Gan (Decis. Support Syst., 2016)

Trinity: Walking on a User-Object-Tag Heterogeneous Network for Personalised Recommendations. - Mingxin Gan; Lily Sun; Rui Jiang 001 (J. Comput. Sci. Technol., 2016)

TAFFY: incorporating tag information into a diffusion process for personalized recommendations. - Mingxin Gan (World Wide Web, 2016)

Mimvec: a deep learning approach for analyzing the human phenome. - Mingxin Gan; Wenran Li; Wanwen Zeng; Xiaojian Wang; Rui Jiang 001 (BMC Syst. Biol., 2017)

A sequence-based method to predict the impact of regulatory variants using random forest. - Qiao Liu 008; Mingxin Gan; Rui Jiang 001 (BMC Syst. Biol., 2017)

Does Daily Travel Pattern Disclose People's Preference? - Mingxin Gan; Ling Gao; Yang Han (HICSS, 2018)

A Random Forest Regression-based Personalized Recommendation Method. - Yingxue Ma; Mingxin Gan (PACIS, 2018)

FLOWER: Fusing global and local associations towards personalized social recommendation. - Mingxin Gan; Rui Jiang 001 (Future Gener. Comput. Syst., 2018)

CDMF: A Deep Learning Model based on Convolutional and Dense-layer Matrix Factorization for Context-Aware Recommendation. - Mingxin Gan; Yingxue Ma; Kejun Xiao (HICSS, 2019)

Gradient Boosting Based Prediction Method for Patient Death in Hospital Treatment. - Yingxue Ma; Mingxin Gan (ICSH, 2019)

R-RNN: Extracting User Recent Behavior Sequence for Click-Through Rate Prediction. - Mingxin Gan; Kejun Xiao (IEEE Access, 2019)

Discovering Memory-Based Preferences for POI Recommendation in Location-Based Social Networks. - Mingxin Gan; Ling Gao (ISPRS Int. J. Geo Inf., 2019)

GLORY: Exploration and integration of global and local correlations to improve personalized online social recommendations. - Mingxin Gan; Lily Sun; Rui Jiang 001 (Inf. Syst. Frontiers, 2019)

Introduction to the Minitrack on Social Media Management in Big Data Era. - Mingxin Gan; Hua Jonathan Ye; Xiangbin Yan (HICSS, 2020)

DeepFusion: Fusing User-Generated Content and Item Raw Content towards Personalized Product Recommendation. - Mingxin Gan; Hang Zhang 022 (Complex., 2020)

Exploring multiple spatio-temporal information for point-of-interest recommendation. - Yingxue Ma; Mingxin Gan (Soft Comput., 2020)

Introduction to the Minitrack on Big Data-driven Social Media Management. - Xiangbin Yan; Mingxin Gan; Hua Ye 001 (HICSS, 2021)

ILFM: Item Attribute-Aware Latent Factor Model for Personalized Recommendation. - O-Chol Kwon; Mingxin Gan; Xiongtao Zhang (PACIS, 2021)

Exploring user movie interest space: A deep learning based dynamic recommendation model. - Mingxin Gan; Hongfei Cui (Expert Syst. Appl., 2021)

DeepAssociate: A deep learning model exploring sequential influence and history-candidate association for sequence recommendation. - Yingxue Ma; Mingxin Gan (Expert Syst. Appl., 2021)

DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers. - Shengquan Chen; Mingxin Gan; Hairong Lv; Rui Jiang 001 (Genom. Proteom. Bioinform., 2021)

Incorporating Memory-Based Preferences and Point-of-Interest Stickiness into Recommendations in Location-Based Social Networks. - Hang Zhang 022; Mingxin Gan; Xi Sun (ISPRS Int. J. Geo Inf., 2021)

Integrating Community Interest and Neighbor Semantic for Microblog Recommendation. - Mingxin Gan; Xiongtao Zhang (Int. J. Web Serv. Res., 2021)

Introduction to the Minitrack on Big Data-driven Social Media Management. - Mingxin Gan; Xiangbin Yan (HICSS, 2022)

Exploring the Influencing Factors of IP Film Rating by Sentiment Analysis and GMM. - Yingxue Ma; Mingxin Gan; Jiao Xv (HICSS, 2022)

DeepInteract: Multi-view features interactive learning for sequential recommendation. - Mingxin Gan; Yingxue Ma (Expert Syst. Appl., 2022)

A knowledge-enhanced contextual bandit approach for personalized recommendation in dynamic domains. - Mingxin Gan; O-Chol Kwon (Knowl. Based Syst., 2022)

Knowledge transfer learning from multiple user activities to improve personalized recommendation. - Mingxin Gan; Yingxue Ma (Soft Comput., 2022)

Mapping user interest into hyper-spherical space: A novel POI recommendation method. - Mingxin Gan; Yingxue Ma (Inf. Process. Manag., 2023)

Mining dynamic preferences from geographical and interactive correlations for next POI recommendation. - Jieyu Ren; Mingxin Gan (Knowl. Inf. Syst., 2023)

A disaggregated interest-extraction network for click-through rate prediction. - Mingxin Gan; Danyang Li; Xiongtao Zhang (Multim. Tools Appl., 2023)

Mining multiple sequential patterns through multi-graph representation for next point-of-interest recommendation. - Mingxin Gan; Caiping Tan (World Wide Web (WWW), 2023)

VIGA: A variational graph autoencoder model to infer user interest representations for recommendation. - Mingxin Gan; Hang Zhang 022 (Inf. Sci., 2023)

Intention-aware denoising graph neural network for session-based recommendation. - Shanshan Hua; Mingxin Gan (Appl. Intell., 2023)

A multi-behavior recommendation method exploring the preference differences among various behaviors. - Mingxin Gan; Gangxin Xu; Yingxue Ma (Expert Syst. Appl., 2023)

MMusic: a hierarchical multi-information fusion method for deep music recommendation. - Jing Xu; Mingxin Gan; Xiongtao Zhang (J. Intell. Inf. Syst., 2023)

Multi-behavior recommendation based on intent learning. - Xinglin Pan; Mingxin Gan (Multim. Syst., 2023)

IDC-CDR: Cross-domain Recommendation based on Intent Disentanglement and Contrast Learning. - Jing Xu; Mingxin Gan; Hang Zhang 022; Shuhao Zhang (Inf. Process. Manag., 2024)

MBDL: Exploring dynamic dependency among various types of behaviors for recommendation. - Hang Zhang 022; Mingxin Gan (Inf. Syst., 2024)

CGG: Category-aware global graph contrastive learning for session-based recommendation. - Mingxin Gan; Xiongtao Zhang; Yuxin Liang (Knowl. Based Syst., 2024)

Hi-GNN: hierarchical interactive graph neural networks for auxiliary information-enhanced recommendation. - Xiongtao Zhang; Mingxin Gan (Knowl. Inf. Syst., 2024)

Exploiting dynamic social feedback for session-based recommendation. - Mingxin Gan; Chunhua Wang; Lingling Yi; Hao Gu (Inf. Process. Manag., 2024)

C-GDN: core features activated graph dual-attention network for personalized recommendation. - Xiongtao Zhang; Mingxin Gan (J. Intell. Inf. Syst., 2024)

SocialCU: integrating commonalities and uniqueness of users and items for social recommendation. - Shuo Li; Mingxin Gan; Jing Xu (World Wide Web (WWW), 2024)

Sequential-hierarchical attention network: Exploring the hierarchical intention feature in POI recommendation. - Yingxue Ma; Mingxin Gan (World Wide Web (WWW), 2024)

Modeling category and multi-level user intentions for session-based recommendation. - Shanshan Hua; Mingxin Gan; Menghan Li (Eng. Appl. Artif. Intell., 2025)

A self-supervised graph-learning method for reliable-relation identification in social recommendation. - Hang Zhang; Mingxin Gan (World Wide Web (WWW), 2025)

Dual-evolution: a deep sequence learning model exploring dual-side evolutions for movie recommendation. - Mingxin Gan; Xiongtao Zhang; Wenyu Wang (Electron. Commer. Res., 2025)