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特聘講座/特聘研究員｜ Distinguished Chair and Distinguished Research Fellows

● Distinguished Professor (特聘教授), EE department, National Taiwan NSC Distinguished Research Award 2009 (國科會傑出研究獎 ),
陳銘憲 Ming-Syan Chen University (2006-present) 2009-2012
● Full Professor, EE department, National Taiwan University Academic Award (教育部學術獎 )，Ministry of Education, 2009
(1997-present) ACM Fellow
特聘研究員兼資訊科技創新研究中心主任 ● President/CEO, Institute for Information Industry, Taiwan (2007- Teco Award (東元獎), Teco Technology Foundation (東元文教基金會),
Distinguished Research Fellow 2008) 2006
Director of Research Center for Information Technology Innovation, Academia Sinica ● Director, Graduate Institute of Communication Engineering (2003- Honorary Medal of Information (資訊榮譽獎章), IICM (中華民國資訊學
會)，2006
2006)
Ph.D., Computer, Information and Control Engineering, University of Michigan, Ann Arbor, MI, USA IEEE Fellow
Tel: +886-2-2651-7640 Pan Wen Yuen Distinguished Research Award (潘文淵研究傑出獎),
Fax: +886-2-2653-4030 Pan Wen Yuen Foundation (潘文淵文教基金會) (2005)
Email: mschen@citi.sinica.edu.tw
http://arbor.ee.ntu.edu.tw/~mschen/

代表著作 Publications

Journal Publications: Conference Publications:
1. C.-H. Chu, H.-P. Hung, and M.-S. Chen, ``A General Framework of 17. J.-W. Huang and M.-S. Chen, ``DPSP: Distributed Progressive Se-
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研究簡介 Research Description Time-variant Bandwidth Allocation in the Data Broadcasting Envi- quential Pattern Mining on the Cloud,’’ Proc. of the 14 Pacific-Asia
Conf. on Knowledge Discovery and Data Mining (PAKDD-10), June
ronment,’’ IEEE Trans. on Knowledge and Data Engineering, Vol. 22,
No. 3, March 2010. 21-24, 2010.
陳銘憲教授在1988年獲得博士學位後即加入IBM Thomas Prof. Chen is recognized as one of the experts in distributed/parallel query process- 2. Y.-H. Chu, Y.-J. Chen, D.-N. Yang, and M.-S. Chen, ``Reducing Re- 18. S.-C. Lin, M.-Y. Yeh and M.-S. Chen, ``Subsequence Matching of
J. Watson Resarch Center 從事研究工作，其主要研究領 ing and data mining with strong research credentials. He has published more than dundancy in Subspace Clustering,’’ IEEE Trans. on Knowledge and StreamSynopses under the Time Warping Distance,’’ Proc. of the 14
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域為資料庫及分散式與平行式之詢問 (query) 處理 (dis- 270 papers and edited two books, and more than 80 of his journal papers are pub- Data Engineering, Vol. 21, No. 10, October 2009. Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PA-
tributed and parallel query processing)。傳統上在處理 lished in major ACM/IEEE journals/transactions. According to Google Scholar, the 3. H.-L. Chen, M.-S. Chen, and S.-C. Lin, ``Catching the Trend: A KDD-10), June 21-24, 2010.
牽涉到很多個 relations 之 distributed query processing， publications of Prof. Chen have received more than 7,000 citations in total. He also Framework for Clustering Concept-Drifting Categorical Data,’’ IEEE 19. C.-J. Wu, J.-M. Ho, and M.-S. Chen,``Time-Critical Data Dissemina-
tion in Cooperative Peer-to-Peer Systems,’’ Proc. of the IEEE Globe-
Trans. on Knowledge and Data Engineering, Vol. 21, No. 5, pp. 652-
主要是用一種稱之為 semi join 之方式來達到減少資料 filed 17 US patents and 7 ROC patents. More information for his research results can 665, May 2009. com 2009, Nov. 30-Dec. 4, 2009.
傳輸量與資料處理量之目的。陳教授提出一個交互執行 be found in http://www.ee.ntu.edu.tw/~mschen. 4. H.-P. Tsai, H.-P. Hung, and M.-S. Chen, ``On Channel Allocation for 20. J.-H. Hsiao and M.-S. Chen, ``Intention-Focused Active Reranking
(interleaving) semijoins 和 joins 的排程概念以提升distrib- Heterogeneous Data Broadcasting,’’ IEEE Trans. on Mobile Comput- for Image Object Retrieval,’’ Proc. of ACM 18th Conference on In-
uted query 之處理速度。此外，陳教授在 parallel query One of Prof. Chen’s works is on developing the framework and algorithms to improve ing, Vol. 8, No. 5, pp. 694-708, May 2009. formation and Knowledge Management (CIKM-09), November 2-6,
2009.
processing及hash apparatus 之具體成果已被實用於產品 the execution of distributed and parallel queries .His distributed query processing 5. C.-M. Hsu and M.-S. Chen, ``On the Design and Applicability of Dis- 21. C.-Y. Tseng and M.-S. Chen,``Incremental SVM Model for Spam De-
tance Functions in High Dimensional Data Space,’’ IEEE Trans. on
並獲得 IBM Research 中最重要的 IBM Outstanding Innova- work goes beyond the traditional paradigm of only using semijoins as reducers for Knowledge and Data Engineering, Vol. 21, No. 4, pp. 523-536, April tection on Dynamic Email Social Networks,’’ Proc. of the 2009 IEEE
tion Award 和許多 Research/Patent Awards 等重要獎項。 query cost reduction. Instead, he combined joins and semijoins as reducers and 2009. International Conference on Social Computing (SocialCom-09), Au-
devised an innovative approach to interleaving a sequence of joins with properly- gust 29-31, 2009.
陳教授在1996年回國任教後和其研究生將此query identified semijoins to minimize the query execution cost. Prof. Chen’s work on par- 6. C.-C. Chen, M.-C. Chen, and M.-S. Chen, ``An Adaptive Threshold 22. J.-H. Hsiao and M.-S. Chen, ``Language-model-based Detection Cas-
Framework for Event Detection Using HMM-based Life Profiles,’’
processing 技術應用於 mobile query 之處理，此點針對 allel query processing exploited three levels of parallelism, namely intra-operator, ACM Trans. on Information Systems, Vol. 27, No. 2, 2009. cade for Efficient Classification of Image-based Spam E-mail,’’ Pro-
行動通訊中資料傳輸非常昂貴之特性，善用 semi join 和 inter-operator, and inter-query levels. The notion of using multiple partitioned hash 7. K.-T. Chuang, J.-L. Huang, and M.-S. Chen, ``Mining Top-k Frequent ceedings of IEEE Intern’l Conf. on Multimedia and Expo (ICME-09),
June 28- July 3, 2009.
資料廣播之原理達到提昇 data push 機制之效率。陳教 tables he proposed has been validated to be a viable approach to significantly re- Patterns in the Presence of the Memory Constraint,’’ Very Large Data
授近年主要投入資料探勘及多媒體網路之研究，所研發 ducing false lock contention. To improve parallel transaction processing, he further Base Journal (VLDBJ), Vol. 17, No. 5, pp. 1321-1344, August 2008. 23. S.-H. Wu, C.-M. Chen, and M.-S. Chen, ``AAA: Asynchronous,
Adaptive, and Asymmetric Power Management for Mobile Ad Hoc
探討資料探勘之技術包括：(1)相關性 (association)，(2) devised a new hash apparatus for an important database product and this appa- 8. J.-L. Hsiao, H.-P. Hung, and M.-S. Chen, ``Versatile Transcoding Networks,’’Proc. of IEEE INFOCOM 2009 (Mini-Conference), April
Proxy for Internet Content Adaptation,’’ IEEE Transaction on Multi-
分類性 (classification)，(3)叢集性 (clustering)、(4)順序 ratus was shown to be able to reduce the locking overhead significantly. He was media , Vol. 10, No. 4, June 2008. 19-25, 2009.
性(sequential pattern)，和(5)使用者移動模式 (user mov- awarded an Outstanding Innovation Award by IBM Corp. for his contributions to 9. I.-S. Wen, J.-W. Huang, and M.-S. Chen, ``Hardware-Enhanced As- 24. M.-Y. Yeh, K.-L. Wu, P. S. Yu, and M.-S. Chen, ``PROUD: A Proba-
ing pattern) 等。這些經由創新探勘方式所得之資訊對於 parallel transaction and query processing. sociation Rule Mining with Hashing and Pipeling,’’ IEEE Trans. on bilistic Approach to Processing Similarity Queries over Uncertain
Data Streams,’’ Proc. of the 12 Intern’l Conf. on Extending Database
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系統資源的規畫、決策支援等皆有極大的助益。在網路 Prof. Chen also conducted pioneering research on data mining. Several association Knowledge and Data Engineering, Vol. 20, No. 6, June 2008. Technology (EDBT-2008), March 23-26, 2009.
多媒體技術方面，主要的研究在於如何儲存與處理多媒 rule mining techniques he proposed have been widely referenced and adopted by 10. D.-N. Yang and M.-S. Chen, ``Efficient Resource Allocation for Wire- 25. J.-H. Hsiao, C.-S. Chen, and M.-S. Chen, ``A Novel Language-Mod-
體資料，以便有效率地提供網路上資料提取和播放。此 subsequent mining works. Prof. Chen pioneered the work on exploring user moving less Multicast,’’ IEEE Trans. on Mobile Computing, Vol 7, No. 4, pp. el-Based Approach for Image Object Mining and Re-Ranking,’’ Proc.
387-400, April 2008.
外，其研究興趣亦包含行動計算系統與 Web 上之 IA (In- pattern both in the Web and in a mobile computing environment, and also contrib- 11. M.-J. Hsieh, M.-S. Chen, and P. S. Yu, ``Approximate Query Process- of the 8th IEEE Intern’l Conf. on Data Mining (ICDM-2008), Decem-
ber 15-19, 2008.
ternet Appliance) 軟硬體之研發。陳教授在資料庫、資料 uted to the areas of Web search and Web content mining. Explicitly, he was among ing in Cube Streams,’’ IEEE Trans. on Knowledge and Data Engi- 26. K.-P. Lin and M.-S. Chen, ``Releasing the SVM Classifier with Priva-
探勘及多媒體網路領域之研究均發表於最受重視之期刊 the very first to explore path traversal pattern mining in the Web, which has later neering, Vol. 19, No. 11, pp. 1557-1570, November 2007. cy-Preservation,’’ Proc. of the 8 IEEE Intern’l Conf. on Data Mining
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及學術會議，且所提出之許多技術都已為學術界廣泛引 spawned a subsequent of studies. He devised a search method VIPAS which builds 12. M.-Y. Yeh, B.-R. Dai, and M.-S. Chen, ``Clustering over Multi- (ICDM-2008), December 15-19, 2008.
用並成為後續重要之研究課題。 ple Evolving Streams by Events and Correlations,’’ IEEE Trans. on 27. C.-M. Hsu and M.-S. Chen, “Efficient Web Matrix Processing based
virtual hyperlinks in light of prior usage of search results to enable itself to render Knowledge and Data Engineering, Vol. 19, No. 10, pp. 1349-1362, on Dual Reordering” Proc. of ACM 17 Conference on Information
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better ranked Web pages to users. His work on sequential data broadcasting has October 2007. and Knowledge Management (CIKM-08), Oct. 26-30, 2008.
been widely cited by recent papers on mobile computing. 13. H.-P. Hung, K.-T. Chuang, and M.-S. Chen, ``Efficient Top-k Query 28. C.-Y. Tseng, M.-S. Chen and P.-J. Sung, “A Novel Email Abstraction
Processing over Multiple Streams with Minimized Global Error,’’ Scheme for Spam Detection” Proc. of ACM 17 Conference on Infor-
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IEEE Trans. on Knowledge and Data Engineering, Vol. 19, No. 10, mation and Knowledge Management (CIKM-08), Oct. 26-30, 2008.
pp. 1404-1419, October 2007.
29. S.-H. Wu, K.-P. Lin, C.-M. Chen, and M.-S. Chen, ``Asymmetric Sup-
14. H.-P. Hung and M.-S. Chen, ``MULS: A General Framework of Pro- port Vector Machines: Low False-Positive Learning Under the User
viding Multi-Level Service Quality in Sequential Data Broadcasting,’’ Tolerance,’’ Proc. of the 14 ACM SIGKDD Intern’l Conf. on Knowl-
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IEEE Trans. on Knowledge and Data Engineering, Vol. 19, No. 10, edge Discovery and Data Mining (KDD-2008), August 24-27, 2008.
pp. 1433-1447, October 2007.
30. M.-Y. Yeh, K.-L. Wu, P. S. Yu, and M.-S. Chen, ``LEEWAVE: Level-
15. J.-L. Huang and M.-S. Chen, ``A QoS-Aware and Energy-Conserved Wise Distribution of Wavelet Coefficients for Processing kNN Que-
Transcoding Proxy Using On-demand Data Broadcasting,’’ IEEE ries over Distributed Streams,’’ Proc. of the 34th Intern’l Conf. on
Trans. on Mobile Computing, Vol. 6, No. 8, pp. 971-987, August Very Large Data Bases (VLDB-2008), August 24-30, 2008.
2007.
16. J.-W. Huang, B.-R. Dai, and M.-S. Chen, ``Twain: Two-End Associa-
tion Miner with Precise Frequent Exhibition Periods,’’ ACM Trans. on
Knowledge Discovery from Data, Vol. 1, No. 2, July 2007.
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