名:李秋丹


        称:副研究员、硕士生导师


    联系电话:010-82449802


    电子邮件:qiudan.li@ia.ac.cn


    联系地址:北京市海淀区中关村东路95号

    邮政编码:100190



[1] Li, Q.D., Wang,C., Liu,R.R., Wang, L., Zeng, D., Leischow, S.,“Understanding users’ vaping experience from social media”, Journal of Medical Internet Research, 2018.
[2] Bai,J., Li, L.J., Zeng, D., Li,Q.D., “Associated activation-driven enrichment: understanding implicit information from a cognitive perspective”, IEEE Transactions on Knowledge and Data Engineering, 2017, vol. 29, no. 12, pp. 2655-2668.
[3] Zhan,Y.C., Liu, R.R., Li, Q.D., Leischow S., Zeng D., “Identifying topics for e-cigarette user-generated contents: a case study from multiple social media platforms”, Journal of Medical Internet Research, 2017, vol.19, no. 1:e24.
[4] Li, Q.D., Jin, Z.P., Wang, C., Zeng, D., “Mining opinion summarizations using convolutional neural networks in chinese microblogging systems”, Knowledge-based Systems, 2016, vol. 107, pp. 289–300.
[5] Li, Q.D., Zhan,Y.C., Wang, L., Leischow S., Zeng, D., “Analysis of symptoms and their potential associations with e-liquids’ components:A Social Media Study”, BMC Public Health, 2016.
[6] Zhang, Z.F., Li, Q.D., Zeng, D., Gao, H., “Extracting evolutionary communities in community question answering”, Journal of the American Society for Information Science and Technology, 2014, vol.65, no.4, pp.1170-1186.
[7] Bao, H.Y., Li, Q.D., Liao,S., Song,S.Y., Gao, H. “A new temporal and social PMF-based method to predict users’ interests in micro-blogging”, Decision Support Systems, 2013, vol.55, no. 3, pp.698-709.
[8] Zhang, Z.F., Li, Q.D., Zeng, D., Gao, H., “User community discovery from multi-relational networks”,Decision Support Systems, 2013, vol. 54, no. 2, pp.870-879.
[9] Lu, D.Y., Li, Q.D., Liao, S.Y., “A Graph-based action network framework to identify prestigious members through member's prestige evolution”, Decision Support Systems, 2012, vol.53, no.1, pp. 44-54.
[10] Zhang, Z.F., Li, Q.D., Zeng, D., “Mining evolutionary topic patterns in community question answering systems”, IEEE Trans. On Systems, Man and Cybernetics-A, 2011, vol.41, no. 5, pp. 828-833.

[1] 发明专利: “基于资源整合与信息传播特征的社区发现及演化方法”, 专利号:ZL201310062057.X,授权日期: 2016.1.20
[2] 发明专利: “一种基于情景信息的个性化资源信息的推荐方法”, 专利号:ZL200910089587.7, 授权日期:2012.6.27
[3] 发明专利: “一种搜索引擎作弊检测的优化方法”,专利号: ZL200810056726.1, 授权日期: 2011. 9.14
[4] 发明专利: “实现观点搜索引擎排序的方法”, 专利号: ZL200810057879.8,授权日期: 2011.8.31
[5] 发明专利: “一种基于小样本集的搜索引擎作弊检测方法”,专利号: ZL200710119196.6, 授权日期: 2011.9.7
打印本页 关闭本页