李圣文 (副教授)

副教授 硕士生导师

性别:男

学历:博士研究生

学位:工学博士学位

所在单位:计算机学院

学科:软件工程 电子信息工程

Email:

个人简历

李圣文,男,软件工程系教师,副教授,博士,硕士生导师,中国计算机学会(CCF)会员,AAG会员。20007-至今,任教于中国地质大学(武汉)计算机学院软件工程系;20151-20161月,赴美国KSU访问学习一年。近年来主持和参与国家自然科学基金面上项目、国家重点研发计划等项目6项;出版教材1部;指导学生在全国高校互联网应用创新大赛等获奖多项。


研究方向    

   [1] 时空大数据挖掘与机器学习

   [2] 自然语言处理与知识图谱


主讲课程

     近年主要主讲本科生《Java与.Net软件开发》、《Web软件开发》、《计算机网络》、《软件测试》、《面向对象软件工程》、《软件工程专业前沿文献》及研究生《高级程序设计》、《知识图谱》等课程及相关实习实践课程。


科研论文        

   

[1].      Li, S., Sun, C., Chen, R., Li, X., Liang, Q., Gong, J., & Yao, H. (2022). Location-aware neural graph collaborative filtering. International Journal of Geographical Information Science, 0(0), 1–25. https://doi.org/10.1080/13658816.2022.2073594

[2].      Li, S., Li, B., Yao, H., Zhou, S., Zhu, J., & Zeng, Z. (2022). Completing WordNets with Sememe Knowledge. Electronics, 11(1), 1–15. https://doi.org/10.3390/electronics11010079

[3].      Fang, F., Zheng, D., Li, S., Liu, Y., Zeng, L., Zhang, J., & Wan, B. (2022). Improved Pseudomasks Generation for Weakly Supervised Building Extraction from High-Resolution Remote Sensing Imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 1629–1642. https://doi.org/10.1109/JSTARS.2022.3144176

[4].      Zhang, X., Zheng, Y., Ye, X., Peng, Q., Wang, W., & Li, S. (2021). Clustering with implicit constraints: A novel approach to housing market segmentation. Transactions in GIS, n/a(n/a). https://doi.org/https://doi.org/10.1111/tgis.12878

[5].      Gong, J., Li, S., Ye, X., Peng, Q., & Kudva, S. (2021). Modelling impacts of high-speed rail on urban interaction with social media in China’s mainland. Geo-Spatial Information Science, 24(4), 638–653. https://doi.org/10.1080/10095020.2021.1972771

[6].      Zhang, X., Zhang, Z. K., Wang, W., Hou, D., Xu, J., Ye, X., & Li, S. (2021). Multiplex network reconstruction for the coupled spatial diffusion of infodemic and pandemic of COVID-19. International Journal of Digital Earth, 14(4), 401–423. https://doi.org/10.1080/17538947.2021.1888326

[7].      Lee, J., Li, S., Wang, S., Wang, J., & Li, J. (2021). Spatio-Temporal Nearest Neighbor Index for Measuring Space-Time Clustering among Geographic Events. Papers in Applied Geography, 7(2), 117–130. https://doi.org/10.1080/23754931.2020.1810112

[8].      Fang, F., Yu, Y., Li, S., Zuo, Z., Liu, Y., Wan, B., & Luo, Z. (2021). Synthesizing location semantics from street view images to improve urban land-use classification. International Journal of Geographical Information Science, 35(9), 1802–1825. https://doi.org/10.1080/13658816.2020.1831515

[9].      Fang, F., Wu, K., Liu, Y., Li, S., Wan, B., Chen, Y., & Zheng, D. (2021). A Coarse-to-Fine Contour Optimization Network for Extracting Building Instances from High-Resolution Remote Sensing Imagery. Remote Sensing, 13(19), 3814. https://doi.org/10.3390/rs13193814

[10].    Dong, L., Yao, H., Li, D., Wang, Y., Li, S., & Liang, Q. (2021). Improving graph neural network via complex-network-based anchor structure. Knowledge-Based Systems, 233, 107528. https://doi.org/10.1016/j.knosys.2021.107528

[11].    Ye, X., Li, S., & Peng, Q. (2021). Measuring interaction among cities in China: A geographical awareness approach with social media data. Cities, 109, 103041. https://doi.org/10.1016/j.cities.2020.103041

[12].    Ye, X., Gong, J., & Li, S. (2021). Analyzing Asymmetric City Connectivity by Toponym on Social Media in China. Chinese Geographical Science, 31(1), 14–26. https://doi.org/10.1007/s11769-020-1172-6

[13].    Yu, Y., Fang, F., Liu, Y., Li, S., & Luo, Z. (2020). Urban Land Use Classification Using Street View Images Based on Deep Transfer Network. In Urban Intelligence and Applications (pp. 83–95). https://doi.org/10.1007/978-3-030-45099-1_7

[14].    Kang, X., Li, B., Yao, H., Liang, Q., Li, S., Gong, J., & Li, X. (2020). Incorporating synonym for lexical sememe prediction: An attention-based model. Applied Sciences (Switzerland), 10(17). https://doi.org/10.3390/app10175996

[15].    Li, S., Chen, R., Wan, B., Gong, J., Yang, L., & Yao, H. (2020). DAWE: A double attention-basedword embedding model with sememe structure information. Applied Sciences (Switzerland), 10(17), 5804. https://doi.org/10.3390/app10175804

[16].    Gong, J., Lee, J., Zhou, S., & Li, S. (2020). Toward measuring the level of spatiotemporal clustering of multi-categorical geographic events. ISPRS International Journal of Geo-Information, 9(7), 440. https://doi.org/10.3390/ijgi9070440

[17].    Zhang, D., Zhang, X., Zheng, Y., Ye, X., Li, S., & Dai, Q. (2020). Detecting intra-urban housing market spillover through a spatial Markov chain model. ISPRS International Journal of Geo-Information, 9(1). https://doi.org/10.3390/ijgi9010056

[18].    Zhen, W., Yang, L., Kwan, M. P., Zuo, Z., Wan, B., Zhou, S., Li, S., Ye, Y., Qian, H., & Pan, X. (2020). Capturing what human eyes perceive: A visual hierarchy generation approach to emulating saliency-based visual attention for grid-like urban street networks. Computers, Environment and Urban Systems, 80(June 2019), 101454. https://doi.org/10.1016/j.compenvurbsys.2019.101454

[19].    Chen, R., Yao, H., Li, R., Kang, X., Li, S., Dong, L., & Gong, J. (2020). Identifying human daily activity types with time-aware interactions. Applied Sciences (Switzerland), 10(24), 1–15. https://doi.org/10.3390/app10248922

[20].    Gong, J., Li, S., & Wan, B. (2019). A Regional Approach to Assessing and Visualizing Spatiotemporal Clustering of Crime Events. Papers in Applied Geography, 5(1–2), 26–44. https://doi.org/10.1080/23754931.2019.1611625

[21].    Gong, J., Li, R., Yao, H., Kang, X., & Li, S. (2019). Recognizing human daily activity using social media sensors and deep learning. International Journal of Environmental Research and Public Health, 16(20), 3955. https://doi.org/10.3390/ijerph16203955

[22].    Ye, X., Li, S., Yang, X., Lee, J., & Wu, L. (2018). The Fear of Ebola: A Tale of Two Cities in China. In Big Data Support of Urban Planning and Management (Issue 2015, pp. 113–132). Springer. https://doi.org/10.1007/978-3-319-51929-6_7

[23].    Gong, J., Li, S., & Lee, J. (2018). Space, time, and disease on social media: A case study of dengue fever in China. Geomatica, 72(4), 112–126. https://doi.org/10.1139/geomat-2018-0016

[24].    Ye, X., Li, S., Sharag-Eldin, A., Tsou, M. H., & Spitzberg, B. (2017). Geography of social media in public response to policy-based topics. In Geospatial Data Science Techniques and Applications (pp. 205–216). https://doi.org/10.1201/b22052

[25].    Lee, J., Gong, J., & Li, S. (2017). Exploring spatiotemporal clusters based on extended kernel estimation methods. International Journal of Geographical Information Science, 31(6), 1154–1177. https://doi.org/10.1080/13658816.2017.1287371

[26].    Li, S., Ye, X., Lee, J., Gong, J., & Qin, C. (2017). Spatiotemporal Analysis of Housing Prices in China: A Big Data Perspective. Applied Spatial Analysis and Policy, 10(3), 421–433. https://doi.org/10.1007/s12061-016-9185-3

[27].    Lee, J., & Li, S. (2017). Extending Moran’s Index for Measuring Spatiotemporal Clustering of Geographic Events. Geographical Analysis, 49(1), 36–57. https://doi.org/10.1111/gean.12106

[28].    李圣文, 凌微, 龚君芳, & 周长征. (2016). 一种基于熵的文本相似性计算方法. 计算机应用研究, 33(03), 665–668.

[29].    Ye, X., Li, S., Yang, X., & Qin, C. (2016). Use of social media for the detection and analysis of infectious diseases in China. ISPRS International Journal of Geo-Information, 5(9), 156. https://doi.org/10.3390/ijgi5090156


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