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何軍,計(jì)算機(jī)工學(xué)博士,數(shù)據(jù)工程與知識(shí)工程教育部重點(diǎn)實(shí)驗(yàn)室主要研究人員。長(zhǎng)期從事數(shù)據(jù)庫(kù)與數(shù)據(jù)挖掘方面的研究,近年主要研究方向?yàn)閿?shù)據(jù)挖掘、數(shù)據(jù)庫(kù)、信息檢索、商務(wù)智能、知識(shí)工程等,在這個(gè)領(lǐng)域積淀了豐富的研究和開(kāi)發(fā)經(jīng)驗(yàn)。主持和參加了近十項(xiàng)科研項(xiàng)目,其中包括973項(xiàng)目、國(guó)家自然科學(xué)基金面上項(xiàng)目、國(guó)家自然科學(xué)基金重大項(xiàng)目、863項(xiàng)目、社科基金重大項(xiàng)目、微軟研究院IFP 課題等。與國(guó)際上多位知名的教授開(kāi)展合作研究,近年在國(guó)際一流學(xué)術(shù)期刊和學(xué)術(shù)會(huì)議,如ACM Transactions oInformatioSystems (TOIS)、IEEE Transactions oKnowledge and Data Engineering (TKDE)、DecisioSupport Systems (DSS)、InformatioSystems、InformatioSciences、Computational Intelligence、Knowledge and InformatioSystems、Electronic Commerce Research and Applications等上發(fā)表多篇論文,在國(guó)際一流學(xué)術(shù)會(huì)議如ACM SIGKDD、IEEE ICDM、SIAM oData Mining (SDM) 、ACM CIKM等發(fā)表論文數(shù)十篇。獲得三次國(guó)際會(huì)議Best Paper Award獎(jiǎng),獲得5項(xiàng)國(guó)家發(fā)明專(zhuān)利授權(quán)。目前是ACM、IEEE等國(guó)際學(xué)術(shù)組織會(huì)員以及中國(guó)計(jì)算機(jī)學(xué)會(huì)高級(jí)會(huì)員。 為本科生、研究生講授包括《數(shù)據(jù)庫(kù)概論》、《商務(wù)智能》、《數(shù)據(jù)挖掘》、《信息檢索》、《計(jì)算廣告學(xué)》、《計(jì)算機(jī)技術(shù)前沿》等課程。
電話(huà): 86-10-62514014
E-mail: hejun@ruc.edu.cn
主要研究方向
數(shù)據(jù)/文本挖掘、商務(wù)智能、社會(huì)網(wǎng)絡(luò)分析、社會(huì)計(jì)算、大數(shù)據(jù)管理與分析、個(gè)性化推薦系統(tǒng)、知識(shí)發(fā)現(xiàn)的理論與應(yīng)用研究。
博士研究生將從事的科研工作及對(duì)學(xué)生的培養(yǎng)要求
1. 有較強(qiáng)的科研能力,能夠熟練閱讀數(shù)據(jù)庫(kù)/數(shù)據(jù)挖掘領(lǐng)域的經(jīng)典論文、當(dāng)前重要國(guó)際會(huì)議(SIGMOD、VLDB、ICDE、SIGKDD、ICDM、SDM、CIKM)和重要學(xué)術(shù)期刊論文,寫(xiě)出高水平的研究綜述,能系統(tǒng)地掌握科學(xué)研究的基本方法并撰寫(xiě)出高水平的學(xué)術(shù)論文。
2. 積極參加國(guó)家科研項(xiàng)目,提高獨(dú)立科研能力特別是創(chuàng)新能力,培養(yǎng)團(tuán)隊(duì)合作精神。
3. 有較強(qiáng)的工程能力,能夠進(jìn)行系統(tǒng)的分析設(shè)計(jì)和開(kāi)發(fā),特別是要通過(guò)項(xiàng)目實(shí)施,提高設(shè)計(jì)和實(shí)現(xiàn)大型軟件的能力。
目前在研的科研項(xiàng)目:
[1] 國(guó)家973項(xiàng)目《海量弱可用信息上知識(shí)發(fā)現(xiàn)、演化與服務(wù)的理論和技術(shù)研究》.項(xiàng)目編號(hào): 2012CB316205
[2] 國(guó)家自然科學(xué)基金項(xiàng)目《通過(guò)社會(huì)化媒體挖掘用戶(hù)興趣的方法及應(yīng)用研究》(項(xiàng)目編號(hào):71272029),
[3] 國(guó)家自然科學(xué)基金重點(diǎn)項(xiàng)目《網(wǎng)絡(luò)信息融合與知識(shí)服務(wù)的理論和方法研究》(項(xiàng)目編號(hào):61033010)
[4] 國(guó)家863項(xiàng)目《基于用戶(hù)興趣模型的媒體大數(shù)據(jù)內(nèi)容整合與可視化技術(shù)》(項(xiàng)目編號(hào):2014AA015204)
[5] 國(guó)家社科基金重大項(xiàng)目《云計(jì)算環(huán)境下的信息資源集成與服務(wù)研究》(項(xiàng)目編號(hào):12&ZD220)
[6] 國(guó)家社科基金重大項(xiàng)目《中華民族偉大復(fù)興的社會(huì)心理促進(jìn)機(jī)制研究》(項(xiàng)目編號(hào):13&ZD155)
[7] 國(guó)家核高基項(xiàng)目:非結(jié)構(gòu)化數(shù)據(jù)管理系統(tǒng)之人大部分,項(xiàng)目編號(hào):2010ZX01042-002-002
近期發(fā)表論文和著作
1.JuHe, H. Liu, Jeffrey Yu, P. Li, W. He, X. Du. Assessing Single-Pair Similarity over Graphs by Aggregating First-Meeting Probabilities. InformatioSystems. Volume 42, June 2014, Pages 107–122.
2.H. Liu, JuHe, D. Zhu, Charles Ling and X. Du. Measuring Similarity Based oLink Information: A Comparative Study. IEEE Transactions oKnowledge and Data Engineering (TKDE). Volume: 25, Issue: 12, 2013, Page(s): 2823–2840.
3.JuHe, H. Liu, Y. Gu, J. Yan, T. Liu. Scalable and Noise Tolerant Web Knowledge Extractiofor Search Task Simplification. DecisioSupport Systems. Volume 56, Pages 156-167. December 2013. (0167-9236).
4.H. Liu, JuHe, T. Wang, W. Song and X. Du. Combining user preferences and user opinions for accurate recommendation. Electronic Commerce Research and Applications. Volume 12, Issue 1, 2013, Pages 14–23.
5.H. Liu, JuHe, Y. Gu, H. Xiong and X. Du. Detecting and Tracking Topics and Events from Web Search Logs. ACM Transactions oInformatioSystems (TOIS). Volume 30 Issue 4, 2012. No. 21.
6.J. Cui, H. Liu, P. Li, JuHe, X. Du, P. Wang. TagClus: a Random Walk-Based Method for Tag Clustering. Knowledge and InformatioSystems. Volume 27, Issue 2 (2011), Page 193–225.
7. JuHe, H. Liu, B. Hu, X. Du and P. Wang. Selecting Effective Features and Relations for Efficient Multi-relational Classification. Computational Intelligence. Volume 26, Number 3, 2010.
8. H. Liu, X. Wang, JuHe, J. Han, D. Xin, Zheng Shao. Top-dowmining of frequent closed patterns from very high dimensional data. InformatioSciences, 15 March 2009.Volume 179, Issue 7, Pages 899–924.
國(guó)際會(huì)議論文選列(Refereed Proceedings with high impact)
1.N. Xu. H. Liu, JuHe and X. Du. Selecting a Representative Set of Diverse Quality Reviews Automatically. SIAM International conference oData Mining (SDM2014). April 24-26, 2014, Philadelphia, Pennsylvania, USA.
2.Y. Li, T. Liu, H. Liu, JuHe and X. Du. Predicting Microblog User's Age based oText Information. The 14th International Conference oWeb InformatioSystem Engineering (WISE 2013), Nanjing, China, 2013, Pages 510-515. (Best Challenge Paper Award).
3.T. Wang, H. Liu, JuHe and X. Du. Mining User Interests from informatioSharing Behaviors iSocial Media. The 17th Pacific-Asia Conference oKnowledge Discovery and Data Mining (PAKDD). April 14–17, 2013, Gold Coast, Australia. (Acceptance Rates: 59/344=17%).
4.X. Jiang, H. Liu, JuHe, X. Du. Effectively Grouping Named Entities from Click-Through Data into Clusters of Generated Keywords. The 16th 2Pacific Asia Conference oInformatioSystems (PACIS). July 11–15, 2012, Vientnam.
5.J. Cui, H. Liu, J. Yan, J. He, at el. Multi-view random walk framework for search task discovery from click-through log. Iproceedings of the 20th ACM Conference oInformatioand Knowledge Management (CIKM). Glasgow, UK. 2011. (Acceptance Rate: 20%).
6.Y. Gu, J. Yan, H. Liu, JuHe, L. Ji, N. Liu, Z. Chen. Extract Knowledge from Semi-structured WebSites for Search Task Simplification. Iproceedings of the 20th ACM Conference oInformatioand Knowledge Management (CIKM). Glasgow, UK. 2011. (Acceptance Rate: 20%)
7.P. Li, Jeffrey Yu, H. Liu, JuHe, X. Du. Ranking Individuals and Groups by Influence Propagation. The Pacific-Asia Conference oKnowledge Discovery and Data Mining (PAKDD). Shenzhen, China. May, 2011. (Acceptance rate: 9.7%).
8.P. Li, H. Liu, Jeffrey Yu, JuHe, X. Du. Fast Single-Pair SimRank Computation. SIAM International conference oData Mining (SDM2010). April 29–May 1, 2010. Columbus, Ohio. pp. 571–582. (Best paper award) (Acceptance rate: 82/351=23.36%).
9. H. Liu, H. Yan, W. Li, W. Wei, JuHe, X. Du. CRO: a System for Online Review Structurization. The 14th ACM SIGKDD International Conference oKnowledge Discovery and Data Mining (SIGKDD), 2008, Las Vegas, USA. p1085–1088. (DEMO).
10. Y. Cai, G. Cong, X. Jia, H. Liu, JuHe, J. Lu and X. Du. Efficient Algorithms for Computing Link-based Similarity iReal World Networks. IEEE International Conference oData Mining (ICDM). Miami, FL, December 6-9, 2009, IEEE Computer Society Press. (Acceptance rate: 139/786=17.68%).
11. P. Li, Y. Cai, H. Liu, JuHe and X. Du. Exploiting the Block Structure of Link Graph for Efficient Similarity Computation. The 13th Pacific-Asia Conference oKnowledge Discovery and Data Mining (PAKDD), Bangkok, Thailand. April 27-30, 2009. (Acceptance Rate: 39/338=11.54%).
15. J. Cui, Pei Li, H. Liu, JuHe, X. Du. A Neighborhood Search Method for Link-Based Tag Clustering. The International Conference oAdvanced Data Mining and Applications (ADMA), August, 2009. Beijing, China. p.91-103. (Best research paper award) (Acceptance rate: 39/322=12%).
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