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2017年10月 — 至今：中國(guó)科學(xué)院計(jì)算技術(shù)研究所，研究員

2012年10月 — 2017年9月 ：中國(guó)科學(xué)院計(jì)算技術(shù)研究所，副研究員

2010年3月 — 2012年9月：中國(guó)科學(xué)院計(jì)算技術(shù)研究所，助理研究員

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2015年9月 — 至今：中國(guó)科學(xué)院大學(xué)，崗位教授

2004年9月— 2010年1月：中國(guó)科學(xué)院計(jì)算技術(shù)研究所，博士生

1999年9月— 2003年7月：西安郵電學(xué)院，計(jì)算機(jī)系，本科生

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【社會(huì)任職】

中國(guó)中文信息社會(huì)媒體處理專委會(huì)副主任

中國(guó)計(jì)算機(jī)學(xué)會(huì)學(xué)術(shù)工作委員會(huì)委員

專著/譯著：

[1] Hua-Wei Shen. Community structure of complex networks. Springer. ISBN: 978-3-642-31820-7.

[2] 沈華偉, 黃俊銘. 《巴拉巴西網(wǎng)絡(luò)科學(xué)》. 河南科學(xué)技術(shù)出版社, 2020. ISBN: 9787534998553

[2] 沈華偉. 《鏈接》. 浙江人民出版社, 2013. ISBN: 978-7-213-05655-0

[3] 王彤彤, 沈華偉, 程學(xué)旗. 《可視化未來(lái)》. 浙江人民出版社, 2015. ISBN: 978-7-213-06850-8

期刊文章:

[1].Hua-Wei Shen, Albert-László Barabási. Collective credit allocation in science. Proc. Natl. Acad. Sci. 111(34): 12325–12330, 2014. (SCI索引，發(fā)表當(dāng)年SCI影響因子：9.737)

[2].Dashun Wang, Chaoming Song, Hua-Wei Shen, Albert-László Barabási. Response to Comment on “Quantifying long-term scientific impact”. Science, 345: 149, 2014. （SCI索引， 發(fā)表當(dāng)年SCI影響因子：31.027）

[3].Huawei Shen, Xueqi Cheng*, Kai Cai, Mao-Bin Hu. Detect overlapping and hierarchical community structure in networks. Physica A, 388(8):1706-1712, 2009. （SCI、EI 索引，發(fā)表當(dāng)年SCI影響因子：1.441）

[4].Hua-Wei Shen*, Xue-Qi Cheng, Jia-Feng Guo. Quantifying and identifying the overlapping community structure in networks. Journal of Statistical Mechanics, P07042, 2009. （SCI索引， 發(fā)表當(dāng)年SCI影響因子：2.758）

[5].Hua-Wei Shen*, Xue-Qi Cheng, Bin-Xing Fang. Covariance, correlation matrix and the multi-scale community structure of networks. Physical Review E, 82(1):016114, 2010. （SCI、EI索引，發(fā)表當(dāng)年SCI影響因子：2.40）

[6].Hua-Wei Shen*, Xue-Qi Cheng. Spectral methods for the detection of network community structure: a comparative analysis. Journal of Statistical Mechanics, P10020, 2010. （SCI 索引， 發(fā)表當(dāng)年SCI影響因子：2.67）

[7].Hua-Wei Shen*, Xue-Qi Cheng, Jia-Feng Guo. Exploring the structural regularities in networks. Physical Review E, 84(5):056111, 2011. （SCI、EI索引，發(fā)表當(dāng)年SCI影響因子：2.352）

[8].Hua-Wei Shen*, Xue-Qi Cheng, Yuan-Zhuo Wang, Yixin Chen. A dimensionality reduction framework for detection of multi-scale structure in heterogeneous networks. Journal of Computer Science and Technology, 27(2): 341-357, 2012. （SCI、EI索引，發(fā)表當(dāng)年SCI 影響因子：0.656）

[9].Xiao-Qian Sun, Hua-Wei Shen*, Xue-Qi Cheng, Yuqing Zhang. Detecting anomalous traders using multi-slice network analysis. Physica A, 473:1-9, 2017.

[10].Hao Wang, Hua-Wei Shen*, Xue-Qi Cheng. Scientific credit diffusion: Researcher level or paper level? Scientometrics, 2016. （SCI索引，發(fā)表當(dāng)年SCI影響因子：2.084）

[11].Xiao-Qian Sun, Hua-Wei Shen*, Xue-Qi Cheng, Yuqing Zhang. Market confidence predicts stock price: beyond supply and demand. PLoS ONE, 2016. （SCI索引，發(fā)表當(dāng)年SCI影響因子：3.057）

[12].Xue-Qi Cheng*, Hua-Wei Shen. Uncovering the community structure associated with the diffusion dynamics on networks. Journal of Statistical Mechanics, P04024, 2010. （SCI索引，發(fā)表當(dāng)年SCI影響因子：2.67）

[13].Bing-Jie Sun, Hua-Wei Shen*, Xue-Qi Cheng. Detecting overlapping communities in massive networks. EPL 108(6):68001, 2014. （SCI索引，發(fā)表當(dāng)年SCI影響因子：2.095）

[14].Xiao-Qian Sun, Hua-Wei Shen*, Xue-Qi Cheng. Trading network predicts stock price. Scientific Reports, 4: 3711, 2014. （SCI 索引，發(fā)表當(dāng)年SCI影響因子：2.927）

[15].Junming Huang, Chao Li, Wenqiang Wang, Hua-Wei Shen*, Guojie Li, Xue-Qi Cheng. Temporal scaling in information propagation. Scientific Reports, 4: 5334, 2014. （SCI索引，發(fā)表當(dāng)年SCI影響因子：2.927）

[16].Peng Bao, Hua-Wei Shen*, Wei Chen, Xueqi Cheng. Cumulative effect in information diffusion: empirical study on a microblogging network. PLoS ONE, 8(10): e76027, 2013. （SCI索引，發(fā)表當(dāng)年SCI影響因子：3.730）

[17].Xiao-Qian Sun, Hua-Wei Shen, Xue-Qi Cheng*, Zhao-Yang Wang. Degree-strength correlation reveals anomalous trading behavior. PLoS ONE, 7(10): e45598, 2012. （SCI索引，發(fā)表當(dāng)年SCI影響因子：4.092）

[18].Fu-Xin Ren*, Hua-Wei Shen, Xue-Qi Cheng. Modeling the clustering in citation networks. Physica A, 391(12): 3533-3539, 2012. （SCI、EI索引，發(fā)表當(dāng)年SCI影響因子：1.522）

[19].Fa-Bin Shi, Xiao-Qian Sun*, Hua-Wei Shen, Xue-Qi Cheng. Detect colluded stock manipulation via clique in trading network. Physica A, 513: 565-571, 2019. （SCI、EI索引，發(fā)表當(dāng)年SCI影響因子：2.924）

[20].Peng Bao*, Hua-Wei Shen, Junming Huang, Haiqiang Chen. Mention effect in information diffusion on a micro-blogging network. PLoS ONE, 13(3):e0194192, 2018. （SCI索引，發(fā)表當(dāng)年SCI影響因子：2.740）

[21].Chengcheng Gou, Huawei Shen, Pan Du, Dayong Wu, Yue Liu, Xueqi Cheng. Learning sequential features for cascade outbreak prediction. Knowledge and Information Systems. 57(3):721-739, 2018. （SCI、EI索引，發(fā)表當(dāng)年SCI影響因子：2.936）

[22].Shenghua Liu*, Huawei Shen*, Houdong Zheng, Xueqi Cheng, Xiangwen Liao*. CT LIS: Learning influences and susceptibilities through temporal behaviors. ACM Transactions on Knowledge Discovery from Data, 13(6): 57, 2019. （SCI、EI索引，發(fā)表當(dāng)年SCI影響因子：2.010）

[23].Yahui Liu, Xiaolong Jin, Huawei Shen. Towards early identification of online rumors based on long short-term memory networks. Information Processing & Management, 56(4):1457-1467, 2019. （SCI、EI索引，發(fā)表當(dāng)年SCI影響因子：4.787）

[24].Shanshan Lyu, Wentao Ouyang, Huawei Shen, Xuqi Cheng. Learning representations for quality estimation of crowdsourced submissions. Information Processing & Management, 56(4): 1484-1493, 2019. （SCI、EI索引，發(fā)表當(dāng)年SCI影響因子：4.787）

[25].Dingda Yang, Xiangwen Liao, Huawei Shen, Xueqi Cheng, Guolong Chen. Relative influence maximization in competitive social networks. Science China - Information Sciences, 60(10): 108101, 2017. （SCI索引，發(fā)表當(dāng)年SCI影響因子：1.628）

[26].Dingda Yang, Xiangwen Liao, Huawei Shen, Xueqi Cheng, Guolong Chen. Modeling the reemergence of information diffusion in social network. Physica A, 2017. (SCI索引，發(fā)表當(dāng)年SCI影響因子：2.243)

[27].Liang Bai, Xueqi Cheng, Jiye Liang, Huawei Shen, Yike Guo. Fast density clustering strategies based on the k-means algorithm. Pattern Recognition, 71:375-386, 2017. （SCI索引，發(fā)表當(dāng)年SCI影響因子：4.582）

[28].Liang Bai, Xueqi Cheng, Jiye Liang, Huawei Shen. An optimization model for clustering categorical data streams with drifting concepts. IEEE Transactions on Knowledge and Data Engineering, 28(11): 2871-2883, 2016. （SCI索引，發(fā)表當(dāng)年SCI影響因子：3.438）

[29].Wei Chen*, Jan Nagler, Xueqi Cheng, Xiaolong Jin, Huawei Shen, Zhiming Zheng, Raissa M. D’Souza. Phase transitions in supercritical explosive percolation. Physical Review E, 87: 052130, 2013. （SCI、EI索引，發(fā)表當(dāng)年SCI影響因子：2.313）

[30].Li Wang*, Jiang Wang, Hua-Wei Shen, Xue-Qi Cheng. An improvement of the fast uncovering community algorithm. Chinese Physics B, 22(10): 108903, 2013. （SCI索引，發(fā)表當(dāng)年SCI影響因子：1.148）

[31].Xueke Xu*, Xueqi Cheng, Songbo Tan, Yue Liu, Huawei Shen. Aspect-level opinion mining of online customer reviews. China Communications, 10(3): 25-41, 2013. （SCI索引，發(fā)表當(dāng)年SCI影響因子：0.464）

[32].Xiao-Qian Sun*, Xue-Qi Cheng, Hua-Wei Shen, Zhao-Yang Wang. Distinguishing manipulated stocks via trading network analysis. Physica A, 390(20): 3427-3434, 2011. （SCI、EI索引，發(fā)表當(dāng)年SCI影響因子：1.373）

[33].Xue-Qi Cheng*, Fu-Xin Ren, Hua-Wei Shen, Zi-Ke Zhang, Tao Zhou. Bridgeness: A local index on edge significance in maintaining global connectivity. Journal of Statistical Mechanics, P10011, 2010. （SCI索引，發(fā)表當(dāng)年SCI影響因子：2.67）

[34].Xiaoqian Sun, Xueqi Cheng*, Huawei Shen, Zhaoyang Wang. Statistical properties of trading activity in Chinese stock market. Physics Procedia, 3(5): 1699–1706, 2010.

[35].沈華偉*, 程學(xué)旗, 陳海強(qiáng), 劉悅. 基于信息瓶頸的社區(qū)發(fā)現(xiàn). 計(jì)算機(jī)學(xué)報(bào), 31(4):677-686, 2008.

[36].徐冰冰, 岑科廷, 黃俊杰, 沈華偉*, 程學(xué)旗. 圖卷積神經(jīng)網(wǎng)絡(luò)綜述. 計(jì)算機(jī)學(xué)報(bào), 43(5): 755-780, 2020.

[37].高金華, 沈華偉, 程學(xué)旗, 劉悅. 基于相似消息的流行度預(yù)測(cè)方法.中文信息學(xué)報(bào). 32(11): 79-85, 2018.

[38].劉雅輝, 靳小龍, 沈華偉, 鮑鵬, 程學(xué)旗. 社交媒體中的謠言識(shí)別研究綜述. 計(jì)算機(jī)學(xué)報(bào). 41(7): 1536-1558, 2018.

[39].程學(xué)旗*, 沈華偉. 復(fù)雜網(wǎng)絡(luò)的社區(qū)結(jié)構(gòu). 復(fù)雜性系統(tǒng)與復(fù)雜性科學(xué), 8(1): 57-70, 2011.

[40].程蘇琦, 沈華偉*, 張國(guó)清, 程學(xué)旗. 符號(hào)網(wǎng)絡(luò)研究綜述. 軟件學(xué)報(bào), 25(1): 1-15, 2014.

[41].滿彤，沈華偉，黃俊銘，程學(xué)旗. SCMF: 一種融合多源數(shù)據(jù)的軟約束矩陣分解推薦算法. 中文信息學(xué)報(bào), 31(4): 174-183, 2017.

[42].王永慶，沈華偉*，程學(xué)旗. 預(yù)測(cè)信息傳播中的轉(zhuǎn)發(fā)選擇. 中文信息學(xué)報(bào). 30(5): 57-64, 2016.

[43].黃俊銘, 沈華偉, 程學(xué)旗. 利用社交網(wǎng)絡(luò)的影響力骨架探索信息傳播. 中文信息學(xué)報(bào), 30(2): 74-82, 2016.

[44].陳友, 沈華偉, 李洋, 程學(xué)旗. 一種高效的面向輕量級(jí)入侵檢測(cè)系統(tǒng)的特征選擇算法. 計(jì)算機(jī)學(xué)報(bào), 30(8):1398-1408, 2007.

[45].王莉*, 程蘇琦，沈華偉，程學(xué)旗. 在線社會(huì)網(wǎng)絡(luò)共演化的結(jié)構(gòu)推斷與預(yù)測(cè). 計(jì)算機(jī)研究與發(fā)展, 50(12): 2492-2503, 2013.

[46].程學(xué)旗, 孫冰杰, 沈華偉, 余智華. 多樣性圖排序的研究現(xiàn)狀及展望. 中國(guó)科學(xué)院院刊, 30(2): 248-256, 2015.

[47].吳瓊, 劉悅, 沈華偉, 張瑾, 許洪波, 程學(xué)旗. 面向跨領(lǐng)域情感分類的統(tǒng)一框架. 計(jì)算機(jī)研究與發(fā)展, 50(8): 1683-1689, 2013.

[48].劉雅輝, 靳小龍, 沈華偉, 鮑鵬, 程學(xué)旗. 社交媒體中的謠言識(shí)別研究綜述. 計(jì)算機(jī)學(xué)報(bào). 2017.

[49].廖祥文, 鄭候東，劉盛華，沈華偉，程學(xué)旗，陳國(guó)龍. 基于用戶行為的情感影響力和易感性學(xué)習(xí). 計(jì)算機(jī)學(xué)報(bào), 40(4): 955-969, 2017

[50].劉瑋, 賀敏, 王麗宏, 劉悅, 沈華偉, 程學(xué)旗. 基于用戶行為特征的微博轉(zhuǎn)發(fā)預(yù)測(cè)研究. 計(jì)算機(jī)學(xué)報(bào), 39(10): 1992-2006, 2016.

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會(huì)議文章：

[1]Huawei Shen*, Dashun Wang, Chaoming Song, Albert-László Barabási. Modeling and predicting popularity dynamics via reinforced Poisson process. Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI 2014), pp. 291-297, July 2014, Québec City, Québec, Canada. (CCF A類會(huì)議)

[2]Liang Hou, Huawei Shen, Xueqi Cheng. Dual Rejection Sampling for Wasserstein Auto-Encoders. Proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), August 29-Septemper 5, 2020, Santiago de Compostela, Spain. (CCF B類會(huì)議)

[3]Hao Wang, Huawei Shen, Xueqi Cheng. Modeling Users’ Multifaceted Interest Correlation for Social Recommendation. Proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2020), pp. 118-129, May 11-14, 2020, Singapore. (CCF C類會(huì)議)

[4]Hao Wang, Huawei Shen, Xueqi Cheng. Modeling POI-Specific Spatial-Temporal Context for Point-of-Interest Recommendation. Proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2020), pp. 130-141, May 11-14, 2020, Singapore. (CCF C類會(huì)議)

[5]Rong Yan, Huawei Shen, Qi Cao, Keting Cen, Li Wang. GraphWGAN: Graph Representation Learning with Wasserstein Generative Adversarial Networks. Proceedings of the 2020 IEEE International Conference on Big Data and Smart Computing (BigComp 2020), pp. 315-322, February 19-22, 2020, South Korea. (Best paper award, second place)

[6]Qi Cao, Huawei Shen, Jinhua Gao, Bingzheng Wei, Xueqi Cheng. Popularity prediction on social platforms with coupled graph neural networks. Proceedings of the 13th International Conference on Web Search and Data Mining (WSDM 2020), pp. 70-78, February 3-7, 2019, Houston, Texas, USA. (CCF B類會(huì)議)

[7]Junjie Huang, Huawei Shen, Liang Hou, Xueqi Cheng. Signed graph attention networks. The 28th International Conference on Artificial Neural Networks (ICANN 2019). pp. 566-577, 2019.

[8]Jiangli Shao, Huawei Shen, Qi Cao, Xueqi Cheng. Temporal Convolutional Networks for Popularity Prediction of Messages on Social Medias. Proceedings of the 25th China Conference on Information Retrieval (CCIR 2019), pp. 135–147, September 20-22, 2019, Fuzhou, China.

[9]Pengfei Wang, Hanxiong Chen, Yadong Zhu, Huawei Shen, Yongfeng Zhang. Unified Collaborative Filtering over Graph Embeddings. Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), July 21–25, 2019, Paris, France. (CCF A類會(huì)議)

[10]Bingbing Xu, Huawei Shen, Qi Cao, Keting Cen, Xueqi Cheng. Graph convolutional networks using heat kernel for semi-supervised learning. Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), pp. 1928-1934, August 10-16, 2019, Macao. (CCF A類會(huì)議)

[11]Shanshan Lyu, Yongqing Wang, Wentao Ouyang, Huawei Shen, Xueqi Cheng. What we vote for? Answer selection from user expertise view in community question answering. Proceedings of the 28th Conference on World Wide Web (WWW 2019), pp. 1198-1209, May 13-17, 2019, San Francisco, USA. (CCF A類會(huì)議)

[12]Yongqing Wang, Huawei Shen, Jinhua Gao, Xueqi Cheng. Learning binary hash codes for fast anchor link retrieval across networks. Proceedings of the 28th Conference on World Wide Web (WWW 2019), pp. 3335-3341, May 13-17, 2019, San Francisco, USA. (CCF A類會(huì)議)

[13]Wenjie Feng, Shenghua Liu, Christos Faloutsos, Bryan Hooi, Huawei Shen, Xueqi Cheng. Beyond outliers and on to micro-clusters: vision-guided anomaly detection. Proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2019), pp. 541–554, April 14-17, 2019, Macau, China.

[14]Bingbing Xu, Huawei Shen, Qi Cao, Yunqi Qiu, Xueqi Cheng. Graph wavelet neural network. The 7th International Conference on Learning Representations (ICLR 2019), May 6-9, 2019, New Orleans, USA.

[15]Hao Wang, Wentao Ouyang, Huawei Shen, Xueqi Cheng. ULE: Learning User and Location Embeddings for POI Recommendation. Proceedings of the 3rd IEEE Third International Conference on Data Science in Cyberspace (DSC 2018), pp. 99-106, June 18-21, 2018, Guangzhou, China.

[16]Shanshan Lyu, Wentao Ouyang, Huawei Shen, Xueqi Cheng. Finding high-quality unstructured submissions in general crowdsourcing tasks. Proceedings of the 24th China Conference on Information Retrieval (CCIR 2018), pp. 198-210, September 27-29, 2018, Guilin, China.

[17]Hao Wang, Huawei Shen, Wentao Ouyang, Xueqi Cheng. Exploiting POI-specific geographical influence for point-of-interest recommendation. Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), pp. 3877-3883, July 13-19, 2018, Stockholm, Sweden. (CCF A類會(huì)議)

[18]Bingjie Sun, Huawei Shen, Jinhua Gao, Wentao Ouyang, Xueqi Cheng. Towards efficient detection of overlapping communities in massive networks. Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI 2018), pp. 418-425, February 2-7, 2018, New Orleans, Louisiana, USA. (CCF A類會(huì)議)

[19]Tong Man, Huawei Shen, Xiaolong Jin, Xueqi Cheng. Cross-domain recommendation: an embedding and mapping approach. Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), pp. 2464-2470, August 19-25, 2017, Melbourne, Australia. (CCF A類會(huì)議)

[20]Yongqing Wang, Huawei Shen, Shenghua Liu, Jinhua Gao, Xueqi Cheng. Cascade dynamics modeling with attention-based recurrent neural network. Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), pp. 2985-2991, August 19-25, 2017, Melbourne, Australia. (CCF A類會(huì)議)

[21]Shenghua Liu, Houdong Zheng, Huawei Shen, Xueqi Cheng, Xiangwen Liao. Learning concise representations of users' influences through online behaviors. Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), pp. 2351-2357, August 19-25, 2017, Melbourne, Australia. (CCF A類會(huì)議)

[22]Qi Cao, Huawei Shen, Hao Gao, Jinhua Gao, Xueqi Cheng. Predicting the Popularity of Online Content with Group-specific Models. Proceedings of the 26th Conference Companion on International World Wide Web (WWW 2017), pp. 765-766, April 3-7, 2017, Perth, Australia. (CCF A類會(huì)議)

[23]Yongqing Wang, Shenghua Liu, Huawei Shen, Jinhua Gao, Xueqi Cheng. Marked Temporal Dynamics Modeling based on Recurrent Neural Network. Proceedings of the 2017 Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2017), pp. 786-798, May 23-26, 2017, Jeju, South Korea.

[24]Yahui Liu, Xiaolong Jin, Huawei Shen, Xueqi Cheng. Do rumors diffuse differently from non-rumors? A systematically empirical analysis in Sina Weibo for rumor identification. Proceedings of the 2017 Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2017), pp. 407-420, May 23-26, 2017, Jeju, South Korea.

[25]Saiping Guan, Xiaolong Jin, Yantao Jia, Yuanzhuo Wang, Huawei Shen, Xueqi Cheng. Self-learning and embedding based entity alignment. Proceedings of the 2017 IEEE International Conference on Big Knowledge (ICBK 2017), August 9-10, 2017, Hefei, China.

[26]Wei Liu, Huawei Shen, Wentao Ouyang, Ge Fu, Li Zha, Xueqi Cheng. Learning Cost-Effective Social Embedding for Cascade Prediction. Proceedings of the 5th National Conference on Social Media Processing (SMP 2016), pp. 1-13, 2016. (Best Paper Award)

[27]Qi Cao, Huawei Shen, Keting Cen, Wentao Ouyang, Xueqi Cheng. DeepHawkes: Bridging the Gap between Prediction and Understanding of Information Cascades. Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2017), Singapore. (CCF B類會(huì)議)

[28]Bingjie Sun, Huawei Shen, Jinhua Gao, Wentao Ouyang, Xueqi Cheng. A Non-negative Symmetric Encoder-Decoder Approach for Community Detection. Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2017), Singapore. (CCF B類會(huì)議)

[29]Shanshan Lyu, Wentao Ouyang, Huawei Shen, Xueqi Cheng. Truth Discovery by Claim and Source Embedding. Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2017), Singapore. (CCF B類會(huì)議)

[30]Tong Man, Huawei Shen, Shenghua Liu, Xiaolong Jin, Xueqi Cheng. Predict anchor links across social networks via an embedding approach. Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), pp. 1823-1829, July 2016, New York City, New York, USA. (CCF A類會(huì)議)

[31]Jinhua Gao, Huawei Shen, Shenghua Liu, Xueqi Cheng. Modeling and predicting retweeting dynamics via a mixture process. Proceedings of the 25th International Conference on World Wide Web (WWW 2016), pp. 33-34, April 2016, Montreal, Canada. (CCF A類會(huì)議)

[32]Yongqing Wang, Huawei Shen*, Shenghua Liu, Xueqi Cheng. Learning user-specific latent influence and susceptibility from information cascades. Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI 2015), pp. 477-483, January 2015, Austin, Texas, USA. (CCF A類會(huì)議)

[33]Suqi Cheng, Huawei Shen*, Junming Huang, Wei Chen, Xueqi Cheng. IMRank: influence maximization via finding self-consistent ranking. Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2014), pp. 475-484, July 2014, Gold Coast, Australia. (CCF A類會(huì)議)

[34]Chao He*, Xueqi Cheng, Jiafeng Guo, Huawei Shen. Multi-select faceted navigation based on minimum description length principle. Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011), pp. 1690-1696, July 2011, Barcelona, Spain. (CCF A類會(huì)議)

[35]Tong Man, Huawei Shen*, Junming Huang, Xueqi Cheng. Context-adaptive matrix factorization for multi-context recommendation. Proceedings of the 24th ACM International Conference on Information and Knowledge Management (CIKM 2015), October 2015, Melbourne, Australia. (CCF B類會(huì)議)

[36]Peng Bao, Hua-Wei Shen*, Xiaolong Jin, Xue-Qi Cheng. Modeling and predicting popularity dynamics of Microblogs using self-excited Hawkes processes. Proceedings of the 24th International Conference on World Wide Web (WWW 2015), pp. 9-10, May 2015, Florence, Italy. (CCF B類會(huì)議)

[37]Suqi Cheng, Huawei Shen*, Junming Huang, Guoqing Zhang, Xueqi Cheng. StaticGreedy: solving the scalability-accuracy dilemma in influence maximization, Proceedings of the 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013), pp. 509-518, October 2013, San Francisco, California. (CCF B類會(huì)議)

[38]Shenghua Liu*, Fuxin Li, Fangtao Li, Xueqi Cheng, Huawei Shen. Adaptive Co-Training SVM for Sentiment Classification on Tweets. Proceedings of the 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013), pp. 2079-2088, October 2013, San Francisco, California. (CCF B類會(huì)議)

[39]Peng Bao, Hua-Wei Shen*, Junming Huang, Xue-Qi Cheng. Popularity prediction in microblogging network: A case study on Sina weibo. Proceedings of the 22nd International Conference on World Wide Web (WWW 2013), pp. 177-178, May 2013, Rio de Janeiro, Brazil. (CCF B類會(huì)議)

[40]Xiaofei zhu*, Jiafeng Guo, Xueqi Cheng, Pan Du, Huawei Shen. A unified framework for recommending diverse and relevant queries. Proceedings of the 20th International Conference on World Wide Web (WWW 2011), pp. 37-46, March 2011, Hyderabad, India. (CCF B類會(huì)議)

[41]Jiafeng Guo*, Xueqi Cheng, Gu Xu, Hua-Wei Shen. A structured approach to query recommendation with social annotation data. Proceedings of the 19th ACM International Conference on Information and Knowledge Management (CIKM 2010), pp. 619-628, October 2010, Toronto, Canada. (CCF B類會(huì)議)

[42]Junming Huang*, Xue-Qi Cheng, Jiafeng Guo, Hua-Wei Shen, Kun Yang. Social recommendation with interpersonal influence. Proceedings of the Nineteenth European Conference on Artificial Intelligence (ECAI 2010), pp. 601-606, August 2010, Lisbon, Portugal. (CCF B類會(huì)議)

[43]Junming Huang*, Xue-Qi Cheng, Hua-Wei Shen, Tao Zhou, Xiaolong Jin. Exploring social influence via posterior effect of word-of-mouth recommendations. Proceedings of the 5th ACM International Conference on Web Search and Data Mining (WSDM 2012), pp. 573-582, February 2012, Seattle, Washington. (CCF C類會(huì)議)

[44]Bing-Jie Sun, Hua-Wei Shen*, Xue-Qi Cheng. Improve network clustering via diversified ranking. Proceedings of the 5th International Conference on Computational Social Networks (CSoNet 2015), pp. 104-114, August 2015, Beijing, China.

[45]Tieying Zhang*, Zhenhua Lv, Huawei Shen, Xueqi Cheng. A white-box empirical study of P2P-VoD systems: several unconventional new findings. Proceedings of the 20th IEEE International Conference on Computer Communication Networks (ICCCN 2011), pp.1-6, July 2011, Maui, Hawaii.

[46]Tong Man*, Hua-Wei Shen, Xue-Qi Cheng. The untold story behind the recommendation in micro-blogging network. In Proceedings of the Second International Conference on Social Computation and its Applications (SCA 2012), pp. 760-764, November 2012, Xiangtan, China.

[47]Jianye Yu*, Yuanzhuo Wang, Jingyuan Li, Huawei Shen, Xueqi Cheng. Analysis of competitive information dissemination in social network based on evolutionary game model. In Proceedings of the Second International Conference on Social Computation and its Applications (SCA 2012), pp. 748-753, November 2012, Xiangtan, China.

[48]Peng Cao*, Shenghua Liu, Jinhua Gao, Huawei Shen, Jingyuan Li, Yue Liu, Xueqi Cheng. Finding topic-related tweets using conversational thread. Intelligent Information Processing (IIP 2012), pp. 258–267, October 2012, Guilin, China.

[49]Huawei Shen, Guoyao Chen, Haiqiang Chen, Yue Liu, Xueqi Cheng. Research on enterprise track of TREC 2007. Proceedings of the Sixteenth Text REtrieval Conference (TREC 2007), 2007.

[50]Haiqiang Chen*, Huawei Shen, Jin Xiong, Songbo Tan, Xueqi Cheng. Social network structure behind the mailing lists: ICT-IIIS at TREC 2006 expert finding track, Proceedings of the 15th Text REtrieval Conference (TREC 2006), 2006.

[1]大數(shù)據(jù)驅(qū)動(dòng)的互聯(lián)網(wǎng)金融監(jiān)測(cè)與服務(wù)平臺(tái)及示范應(yīng)用，國(guó)家自然科學(xué)基金重大研究計(jì)劃集成項(xiàng)目，2018.1-2021.12，經(jīng)費(fèi)900萬(wàn)元

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2019年? 入選北京智源人工智能研究院青年科學(xué)家

2017年? 入選中國(guó)科學(xué)院王寬誠(chéng)率先人才計(jì)劃“盧嘉錫國(guó)際團(tuán)隊(duì)”

2017年? 中科院計(jì)算所“優(yōu)秀科研人員”

2016年? 中科院計(jì)算所“優(yōu)秀科研人員”

2015年? 中國(guó)科學(xué)院青年創(chuàng)新促進(jìn)會(huì)優(yōu)秀會(huì)員

2015年? 北京市科學(xué)技術(shù)二等獎(jiǎng)

2014年? 中國(guó)中文信息學(xué)會(huì)錢偉長(zhǎng)中文信息處理科學(xué)技術(shù)一等獎(jiǎng)

2014年? 中科院計(jì)算所“優(yōu)秀科研人員”

2013年? UCAS-Springer優(yōu)秀博士論文獎(jiǎng)

2012年? 中國(guó)科學(xué)院計(jì)算技術(shù)研究所 “學(xué)術(shù)百星”

2011年? 入選首批中國(guó)科學(xué)院青年創(chuàng)新促進(jìn)會(huì)

2011年? 中國(guó)電子學(xué)會(huì)科學(xué)技術(shù)一等獎(jiǎng)

2011年? 中國(guó)計(jì)算機(jī)學(xué)會(huì)優(yōu)秀博士論文提名獎(jiǎng)

2011年? 中國(guó)科學(xué)院優(yōu)秀博士論文獎(jiǎng)

2010年? 中科院計(jì)算所“優(yōu)秀科研人員”

2010年? 中國(guó)科學(xué)院院長(zhǎng)特別獎(jiǎng)