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Mingxin Gan
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2020 – today
- 2024
- [j43]Mingxin Gan
, Chunhua Wang
Exploiting dynamic social feedback for session-based recommendation. Inf. Process. Manag. 61(2): 103632 (2024) - [j42]Jing Xu, Mingxin Gan
IDC-CDR: Cross-domain Recommendation based on Intent Disentanglement and Contrast Learning. Inf. Process. Manag. 61(6): 103871 (2024) - [j41]Hang Zhang
MBDL: Exploring dynamic dependency among various types of behaviors for recommendation. Inf. Syst. 124: 102407 (2024) - [j40]Xiongtao Zhang, Mingxin Gan:
C-GDN: core features activated graph dual-attention network for personalized recommendation. J. Intell. Inf. Syst. 62(2): 317-338 (2024) - [j39]Xiongtao Zhang, Mingxin Gan:
Hi-GNN: hierarchical interactive graph neural networks for auxiliary information-enhanced recommendation. Knowl. Inf. Syst. 66(1): 115-145 (2024) - [j38]Yingxue Ma, Mingxin Gan:
Sequential-hierarchical attention network: Exploring the hierarchical intention feature in POI recommendation. World Wide Web (WWW) 27(6): 67 (2024) - [j37]Shuo Li, Mingxin Gan, Jing Xu:
SocialCU: integrating commonalities and uniqueness of users and items for social recommendation. World Wide Web (WWW) 27(6): 71 (2024) - 2023
- [j36]Shanshan Hua, Mingxin Gan
Intention-aware denoising graph neural network for session-based recommendation. Appl. Intell. 53(20): 23097-23112 (2023) - [j35]Mingxin Gan
A multi-behavior recommendation method exploring the preference differences among various behaviors. Expert Syst. Appl. 228: 120316 (2023) - [j34]Mingxin Gan
Mapping user interest into hyper-spherical space: A novel POI recommendation method. Inf. Process. Manag. 60(2): 103169 (2023) - [j33]Mingxin Gan
VIGA: A variational graph autoencoder model to infer user interest representations for recommendation. Inf. Sci. 640: 119039 (2023) - [j32]Jing Xu, Mingxin Gan, Xiongtao Zhang:
MMusic: a hierarchical multi-information fusion method for deep music recommendation. J. Intell. Inf. Syst. 61(3): 795-818 (2023) - [j31]Jieyu Ren
Mining dynamic preferences from geographical and interactive correlations for next POI recommendation. Knowl. Inf. Syst. 65(1): 183-206 (2023) - [j30]Xinglin Pan, Mingxin Gan:
Multi-behavior recommendation based on intent learning. Multim. Syst. 29(6): 3655-3668 (2023) - [j29]Mingxin Gan
A disaggregated interest-extraction network for click-through rate prediction. Multim. Tools Appl. 82(18): 27771-27793 (2023) - [j28]Mingxin Gan
Mining multiple sequential patterns through multi-graph representation for next point-of-interest recommendation. World Wide Web (WWW) 26(4): 1345-1370 (2023) - 2022
- [j27]Mingxin Gan, Yingxue Ma:
DeepInteract: Multi-view features interactive learning for sequential recommendation. Expert Syst. Appl. 204: 117305 (2022) - [j26]Mingxin Gan
A knowledge-enhanced contextual bandit approach for personalized recommendation in dynamic domains. Knowl. Based Syst. 251: 109158 (2022) - [j25]Mingxin Gan
Knowledge transfer learning from multiple user activities to improve personalized recommendation. Soft Comput. 26(14): 6547-6566 (2022) - [c16]Mingxin Gan, Xiangbin Yan:
Introduction to the Minitrack on Big Data-driven Social Media Management. HICSS 2022: 1-2 - [c15]Yingxue Ma, Mingxin Gan, Jiao Xv:
Exploring the Influencing Factors of IP Film Rating by Sentiment Analysis and GMM. HICSS 2022: 1-7 - 2021
- [j24]Mingxin Gan
Exploring user movie interest space: A deep learning based dynamic recommendation model. Expert Syst. Appl. 173: 114695 (2021) - [j23]Yingxue Ma, Mingxin Gan:
DeepAssociate: A deep learning model exploring sequential influence and history-candidate association for sequence recommendation. Expert Syst. Appl. 185: 115587 (2021) - [j22]Shengquan Chen
DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers. Genom. Proteom. Bioinform. 19(4): 565-577 (2021) - [j21]Hang Zhang
Incorporating Memory-Based Preferences and Point-of-Interest Stickiness into Recommendations in Location-Based Social Networks. ISPRS Int. J. Geo Inf. 10(1): 36 (2021) - [j20]Mingxin Gan
Integrating Community Interest and Neighbor Semantic for Microblog Recommendation. Int. J. Web Serv. Res. 18(2): 54-75 (2021) - [c14]Xiangbin Yan, Mingxin Gan, Hua Ye:
Introduction to the Minitrack on Big Data-driven Social Media Management. HICSS 2021: 1-2 - [c13]O-Chol Kwon, Mingxin Gan, Xiongtao Zhang:
ILFM: Item Attribute-Aware Latent Factor Model for Personalized Recommendation. PACIS 2021: 199 - 2020
- [j19]Mingxin Gan
DeepFusion: Fusing User-Generated Content and Item Raw Content towards Personalized Product Recommendation. Complex. 2020: 4780191:1-4780191:12 (2020) - [j18]Yingxue Ma, Mingxin Gan
Exploring multiple spatio-temporal information for point-of-interest recommendation. Soft Comput. 24(24): 18733-18747 (2020) - [c12]Mingxin Gan, Hua Jonathan Ye, Xiangbin Yan:
Introduction to the Minitrack on Social Media Management in Big Data Era. HICSS 2020: 1
2010 – 2019
- 2019
- [j17]Mingxin Gan
R-RNN: Extracting User Recent Behavior Sequence for Click-Through Rate Prediction. IEEE Access 7: 111767-111777 (2019) - [j16]Mingxin Gan
Discovering Memory-Based Preferences for POI Recommendation in Location-Based Social Networks. ISPRS Int. J. Geo Inf. 8(6): 279 (2019) - [j15]Mingxin Gan
GLORY: Exploration and integration of global and local correlations to improve personalized online social recommendations. Inf. Syst. Frontiers 21(4): 925-939 (2019) - [c11]Mingxin Gan, Yingxue Ma, Kejun Xiao:
CDMF: A Deep Learning Model based on Convolutional and Dense-layer Matrix Factorization for Context-Aware Recommendation. HICSS 2019: 1-8 - [c10]Xiangbin Yan, Mingxin Gan, Hua Jonathan Ye:
Introduction to the Minitrack on Social Media Management in Big Data Era. HICSS 2019: 1-2 - [c9]Yingxue Ma, Mingxin Gan:
Gradient Boosting Based Prediction Method for Patient Death in Hospital Treatment. ICSH 2019: 283-293 - 2018
- [j14]Mingxin Gan
FLOWER: Fusing global and local associations towards personalized social recommendation. Future Gener. Comput. Syst. 78: 462-473 (2018) - [c8]Mingxin Gan, Ling Gao, Yang Han:
Does Daily Travel Pattern Disclose People's Preference? HICSS 2018: 1-10 - [c7]Yingxue Ma, Mingxin Gan:
A Random Forest Regression-based Personalized Recommendation Method. PACIS 2018: 170 - 2017
- [j13]Qiao Liu
A sequence-based method to predict the impact of regulatory variants using random forest. BMC Syst. Biol. 11(S-2): 7:1-7:9 (2017) - [j12]Mingxin Gan, Wenran Li
Mimvec: a deep learning approach for analyzing the human phenome. BMC Syst. Biol. 11(S-4): 3-16 (2017) - 2016
- [j11]Mingxin Gan:
COUSIN: A network-based regression model for personalized recommendations. Decis. Support Syst. 82: 58-68 (2016) - [j10]Mingxin Gan, Lily Sun, Rui Jiang
Trinity: Walking on a User-Object-Tag Heterogeneous Network for Personalised Recommendations. J. Comput. Sci. Technol. 31(3): 577-594 (2016) - [j9]Mingxin Gan:
TAFFY: incorporating tag information into a diffusion process for personalized recommendations. World Wide Web 19(5): 933-955 (2016) - 2015
- [j8]Mingxin Gan
ROUND: Walking on an object-user heterogeneous network for personalized recommendations. Expert Syst. Appl. 42(22): 8791-8804 (2015) - [j7]Mingxin Gan, Le Li:
Motif-Plus: incorporation of network motifs into top-n friendship recommendations. Int. J. Reason. based Intell. Syst. 7(3/4): 315-324 (2015) - 2014
- [j6]Mingxin Gan
Correlating Information Contents of Gene Ontology Terms to Infer Semantic Similarity of Gene Products. Comput. Math. Methods Medicine 2014: 891842:1-891842:9 (2014) - 2013
- [j5]Mingxin Gan, Rui Jiang
Improving accuracy and diversity of personalized recommendation through power law adjustments of user similarities. Decis. Support Syst. 55(3): 811-821 (2013) - [j4]Mingxin Gan, Rui Jiang
Constructing a user similarity network to remove adverse influence of popular objects for personalized recommendation. Expert Syst. Appl. 40(10): 4044-4053 (2013) - [c6]Mingxin Gan, Rui Jiang
Inferring semantic similarity through correlating information contents of gene ontology terms. BIBM 2013: 1-5 - 2012
- [j3]Rui Jiang
Identification of disease-related nsSNPs via the integration of protein sequence features and domain-domain interaction data. Int. J. Comput. Biol. Drug Des. 5(3/4): 206-221 (2012) - [c5]Mingxin Gan, Xue Dou, Rui Jiang
Improving Recommendation Performance through Ontology-Based Semantic Similarity. ICICA (LNCS) 2012: 203-210 - [c4]Yue Huang, Mingxin Gan, Rui Jiang
Ontology-Based Genes Similarity Calculation with TF-IDF. ICICA (LNCS) 2012: 600-607 - 2011
- [j2]Rui Jiang
Constructing a gene semantic similarity network for the inference of disease genes. BMC Syst. Biol. 5(S-2): S2 (2011) - [j1]Jiaxin Wu, Mingxin Gan, Rui Jiang
Prioritisation of candidate Single Amino Acid Polymorphisms using one-class learning machines. Int. J. Comput. Biol. Drug Des. 4(4): 316-331 (2011) - [c3]Mingxin Gan, Xue Dou, Daoping Wang, Rui Jiang
DOPCA: A New Method for Calculating Ontology-Based Semantic Similarity. ACIS-ICIS 2011: 110-115 - [c2]Jiaxin Wu, Mingxin Gan, Rui Jiang
A genetic algorithm for optimizing subnetwork markers for the study of breast cancer metastasis. ICNC 2011: 1578-1582
2000 – 2009
- 2009
- [c1]Mingxin Gan:
Enterprise Isomorphic Mapping Mechanism: Towards Ontology Interoperability in EIS Development. ICEBE 2009: 340-345
Coauthor Index
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