EDWARD
HUNG
Department of Computing
The
Hung Hom,
PUBLICATIONS
Refereed Journal Articles
1. Edward Hung, Lurong
Xiao and Regant Y.S. Hung, “An Efficient
Representation Model of Distance Distribution Between
Uncertain Objects”, to appear in Computational
Intelligence.
2. Wai Kit
Wong, David W. Cheung, Edward Hung, Ben Kao, Nikos Mamoulis,
“An Audit Environment for Outsourcing of
Frequent Itemset Mining”, to appear in the Proceedings of the VLDB Endowment (PVLDB), Vol. 2, issue 1, 2009.
3. Edward
Hung, Lise
Getoor, V.S. Subrahmanian, "Probabilistic
Interval XML", in ACM Transactions on Computational Logic (TOCL),
Volume 8, Issue 4, Article 24, pages 1-38, Aug 2007.
4. Edward
Hung, David W. Cheung, Ben Kao, "Optimization in Data Cube System Design", in Journal of Intelligent Information Systems (JIIS),
Kluwer Academic Publishers, Volume 23, Issue 1, pages
17-45, July 2004.
Cited by:
·
Ruey-Shun
Chen, Yung-Shun Tsai, "The Application of Data Mining Technology for
Intelligent Enterprise Resource Planning System", in Proc. of the IEEE International Conference on Signal-image Technology
and Internet-based systems (SITIS'05), Yaoundé Cameroon, Nov 27 - Dec 1,
2005.
5. Edward
Hung, David W. Cheung, "Parallel Mining of Outliers in
Large Database", in Distributed and Parallel Database (DAPD), Kluwer Academic Publishers, Volume 12, Issue 1, pages 5-26,
July 2002.
Cited by:
·
M. Agyemang,
K. Barker and R. Alhajj, “A comprehensive survey of
numeric and symbolic outlier mining techniques”, in Intelligent Data Analysis, 10(6):521-538, 2006.
·
Elio
Lozano and Edgar Acuna, "Parallel Algorithms for
distance-based and density-based outliers", in Proc. of the 5th IEEE International Conference on Data Mining,
November 2005.
·
Hu Yang
and Ting Yang, "Outlier Mining Based on Principal Component
Estimation", in Acta Mathematicae Applicatae Sinica (English
Series), Springer-Verlag, Volume 21, Number 2,
Pages 303-310, May 2005.
·
Yufeng Kou,
Chang-Tien Lu, S. Sirwongwattana,
Yo-Ping Huang, “Survey of fraud detection
techniques”, in Proceedings of 2004 IEEE International Conference on
Networking, Sensing and Control, pp. 749-754, 2004.
·
Yan-Xia Zhang, A.-Li Luo,
Yong-Heng Zhao, “Outlier detection in astronomical
data”, in Ground-based Telescopes,
edited by Oschmann, Jacobus
M., Jr. Proceedings of the SPIE, Volume 5493, pp. 521-529, 2004.
Refereed Conference Papers
1.
Yan Li, Edward Hung, “Building A Decision Cluster Forest Model
to Classify High Dimensional Data with Multi-classes”, to appear in Proceedings of The 1st Asian Conference on
Machine Learning (ACML'09), Nanjing,
China, November 2-4, 2009. (acceptance rate = 29 / 113
= 25.7%)
2.
Wai Kit
Wong, David Wai Lok Cheung,
Edward Hung, Ben Kao, Nikos Mamoulis, “An Audit
Environment for Outsourcing of Frequent Itemset Mining”, to appear in Proceedings of the 35th International Conference on Very Large
Data Bases (VLDB), Lyon,
France, August 24-28, 2009.
3.
Chi Cheong Szeto
and Edward Hung, “Mining Outliers with Faster Cutoff
Update and Space Utilization”, in the Proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery
and Data Mining (PAKDD-2009), Bangkok, Thailand, April 27-30, 2009. (Lecture
Notes in Computer Science 5476:823-830
Springer, 2009)
(acceptance rate = 33% of 338 submissions)
4.
Yan Li, Edward Hung, Korris
Chung, Joshua Huang, “Building A Decision Cluster
Classification Model for High Dimensional Data by A Variable Weighting k-Means
Method”, in the Proceedings of
the Twenty-First Australasian Joint Conference on Artificial Intelligence, pages 337-347, Auckland, December
1-5, 2008. (acceptance rate = 42/143 = 29%)
5.
Wai Kit
Wong, David W. Cheung, Edward Hung, and Huan Liu, “Protecting
Privacy in Incremental Maintenance for Distributed Association Rule Mining”,
to appear in the Proceedings of the 12th
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2008),
Osaka, Japan, May 20-23, 2008. (acceptance rate = 12% of 312 submissions)
6.
Edward Hung and Lurong
Xiao, "An
Efficient Representation Model of Distance Distribution Between Two Uncertain
Objects", to appear in Proceedings of IEEE First Pacific-Asia Workshop
on Web Mining and Web-based Application 2008 (WMWA’08), in conjunction with the 12th Pacific-Asia Conference on
Knowledge Discovery and Data Mining (PAKDD-2008), Osaka, Japan, May 20, 2008.
7.
Lurong Xiao
and Edward Hung, "Clustering
Web-Search Results Using Transduction-Based Relevance Model", to
appear in Proceedings of IEEE First Pacific-Asia Workshop on Web Mining and
Web-based Application 2008 (WMWA’08),
in conjunction with the 12th Pacific-Asia Conference on Knowledge Discovery and
Data Mining (PAKDD-2008), Osaka, Japan, May 20, 2008.
8.
Wai Kit
Wong, David W. Cheung, Edward Hung, Ben Kao, Nikos Mamoulis,,
“Security
in Outsourcing of Association Rule Mining”, to appear in the Proceedings of the 33rd International
Conference on Very Large Data Bases (VLDB), Sep 23-28 2007, University of
Vienna, Austria.
9.
Chun-Kit Chui, Ben Kao, Edward Hung, “Mining Frequent Itemsets from Uncertain Data”,
to appear in the Proceedings of the 11th
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2007),
Cited by:
·
10. Lurong
Xiao, Edward Hung, “An Efficient
Distance Calculation Method for Uncertain Objects”, in the Proceedings of 2007 IEEE Symposium on
Computational Intelligence and Data Mining (CIDM),
11. Octavian
Udrea, Yu Deng, Edward Hung, V.S. Subrahmanian, “Probabilistic
Ontologies and Relational Databases”, in the Proceedings of the OTM Confederated International Conferences (CoopIS, DOA, and ODBASE) 2005,
Cited by:
·
Thomas Lukasiewicz,
“Expressive probabilistic description logics”, in Artificial Intelligence,
Volume 172, Issues 6-7, April 2008, Pages 852-883.
·
Alexander Brodsky, X. Sean Wang,
“Decision-Guidance Management Systems (DGMS): Seamless Integration of Data
Acquisition, Learning, Prediction and Optimization”, in Proceedings of the 41st
Annual Hawaii International Conference on System Sciences, pp.71-71, 7-10 Jan.
2008.
·
Thomas Lukasiewicz,
“Tractable Probabilistic Description Logic Programs”, in Proceedings of the
First International Conference, SUM 2007, Washington,DC,
USA, October 10-12, 2007.
12. Edward
Hung, Yu Deng, V.S. Subrahmanian, "RDF
Aggregate Queries and Views", in the Proceedings of the 21st International
Conference on Data Engineering (ICDE), pages 717-728,
Cited by:
·
Lefteris Sidirourgos, George Kokkinidis,
Theodore Dalamagas, Vassilis
Christophides, "Indexing views to route queries
in a PDMS", in Distributed and Parallel Databases, Volume 23, Issue 1,
pages 45-68, Feb 21, 2008.
·
Dawit Seid, Sharad Mehrotra,
"Grouping and Aggregate queries Over Semantic Web Databases ", in
Proceedings of International Conference on Semantic Computing (ICSC 2007),
pages 775-782, 2007.
·
Tim Furche,
François Bry, and Oliver Bolzer,
"XML Perspectives on RDF Querying: Towards integrated Access to Data and
Metadata on the Web", in Proceedings
of Workshop über Grundlagen von Datenbanken (GvB2005),
·
Tim Furche,
François Bry, and Oliver Bolzer,
"Marriages of convenience: Triples and graphs, RDF and XML in Web
querying", in Proceedings of
Principles and Practice of Semantic Web Reasoning, Lecture Notes in
Computer Science 3703: 72-84, 2005
13. Edward
Hung, Yu Deng, V.S. Subrahmanian, "TOSS: An
Extension of TAX with Ontologies and Similarity Queries", in the
Proceedings of the 23rd ACM SIGMOD International Conference on
Management of Data, Paris, France, pages 719-730, June 13-18, 2004. (acceptance rate = 69/431 = 16%)
Cited by:
·
Sihem Amer-Yahia, Emiran Curtmola, Alin Deutsch,
"Flexible and efficient XML search with complex full-text
predicates", in Proceedings of the
2006 ACM SIGMOD international conference on Management of data, 2006.
·
C. Farkas, V. Gowadia, A. Jain, and D. Roy, “From XML to RDF: Syntax, Semantics, Security and Integrity”,
(Invited paper) In Proceedings of IFIP TC-11 WG 11.1 & WG 11.5 Joint
Working Conference on Security Management, Integrity, and Internal Control in
Information Systems, Fairfax, Virginia, December 1, 2005.
·
H.P. Chen, J.G. Gu,
X.H. Li, et al., "An XML query mechanism with ontology integration",
in Proceedings of Workshops of Parallel
and Distributed Processing and Applications (ISPA) 2005, Lecture Notes in
Computer Science 3759: 569 - 578, 2005.
14. Edward
Hung, Lise Getoor, V.S. Subrahmanian, "PXML: A Probabilistic
Semistructured Data Model and Algebra", in the Proceedings of the 19th International
Conference on Data Engineering (ICDE),
Cited by:
·
Nilesh N. Dalvi, Dan Suciu, “Efficient
query evaluation on probabilistic databases”, in the International Journal on
Very Large Data Bases (VLDBJ), Volume 16, Number 4, pages 523-544, October,
2007
·
Prithviraj Sen, Amol Deshpande,
“Representing and Querying Correlated Tuples in
Probabilistic Databases”, in Proceedings of 2007 IEEE 23rd International
Conference on Data Engineering (ICDE), pages 596-605, 2007.
·
Ander de Keijzer,
Maurice van Keulen, “User Feedback in Probabilistic
Integration”, in Proceedings of 18th International Conference on Database and
Expert Systems Applications (DEXA '07) , pp.377-381, 3-7 Sept. 2007.
·
Nilesh N. Dalvi, Dan Suciu,
"Management of probabilistic data: foundations and challenges", in Proceedings of the Twenty-Sixth ACM
Symposium on Principles of Database Systems (PODS), June 11-13, 2007,
Beijing, China, pages 1-12.
·
Pierre Senellart,
Serge Abiteboul, "On the complexity of managing probabilistic
XML data", in Proceedings of the
Twenty-Sixth ACM Symposium on Principles of Database Systems (PODS), June
11-13, 2007, Beijing, China, pages 283-292.
·
Matteo Magnani and Danilo Montesi, “An Overview of Imperfection Representation in Semistructured Data”, in Flexible Databases Supporting
Imprecision and Uncertainty, Springer
·
Serge Abiteboul,
Pierre Senellart, “Querying and Updating
Probabilistic Information in XML”, in Proceedings of 10th International
Conference on Extending Database Technology, Munich, Germany, 26-31 March, 2006
·
Sunil Choenni,
Henk Ernst Blok and Erik Leertouwer,
“Handling Uncertainty and Ignorance in Databases: A Rule to Combine Dependent
Data”, in Proceedings of 11th International Conference, DASFAA 2006,
·
Andreas Schmidt, "Ontology-Based
User Context Management: The Challenges of Imperfection and
Time-Dependence", in Proc. of OTM
Conferences,
·
Wang Kay Ngai,
Ben Kao, Chun Kit Chui, Reynold Cheng, Michael Chau, Kevin Y. Yip, "Efficient Clustering of Uncertain
Data", in Sixth IEEE International Conference on Data Mining (ICDM'06),
pages 436-445 2006.
·
Reynold
Cheng, S. Singh, Sunil Prabhakar, R. Shah, J. Vitter
and Y. Xia, "Efficient Join Processing over Uncertain Data", in the ACM 15th Conf. on Information and
Knowledge Management, Arlington, USA 2006.
·
Denilson Barbosa, Alberto O. Mendelzon,
"Declarative generation of synthetic XML data", in Software: Practice and Experience,
Volume 36, Issue 10 , Pages 1051 - 1079, 2006.
·
Michael Chau, Reynold Cheng , Ben Kao and Jackey Ng, “Uncertain Data Mining: An Example in Clustering
Location Data”, in Proceedings of 10th Pacific-Asia Conference, PAKDD 2006,
·
Alex Dekhtyar,
Krol Kevin Mathias, Praveen Gutti,
“Structured Queries for Semistructured Probabilistic
Data”, in Proceedings of the second Twente Data
Management Workshop”, 2006.
·
Andreas Schmidt, “Ontology-Based User
Context Management: The Challenges of Imperfection and Time-Dependence”, in
Proceedings of OTM Confederated International Conferences, CoopIS,
DOA, GADA, and ODBASE 2006, Montpellier, France, October 29 - November 3, 2006.
·
S. Abiteboul and
P. Senellart, “Querying and Updating Probabilistic
Information in XML”. Technical Report 435, GEMO, Inria
Futurs,
·
M. van Keulen,
A. de Keijzer, W. Alink, “A
probabilistic XML approach to data integration”, in Proceedings of the International Conference on Data Engineering, ICDE
2005, April 2005.
·
Matteo Magnani, Danilo Montesi, “A model for imperfect XML data based on Dempster-Shafer’s theory of evidence”, Technical Report
UBLCS-2005-19,
·
Matteo Magnani, Danilo Montesi, "Dimensions of Ignorance in a Semi-Structured
Data Model", in Proceedings of the
Database and Expert Systems Applications, 15th International Workshop on
(DEXA'04), pages: 933-937, 2004.
15. Edward
Hung, Lise Getoor, V.S. Subrahmanian, "Probabilistic Interval XML", in the Proceedings of the Ninth International
Conference on Database Theory (ICDT), Siena, Italy, January 8-10, 2003
(Lecture Notes in Computer Science 2572: 361-377, 2003). (acceptance
rate = 26/91 = 29%)
Cited by:
·
Nilesh N. Dalvi, Dan Suciu, “Efficient
query evaluation on probabilistic databases”, in the International Journal on
Very Large Data Bases (VLDBJ), Volume 16, Number 4, pages 523-544, October,
2007
·
Nilesh Dalvi, Dan Suciu, "Efficient
Query Evaluation on Probabilistic Databases", to appear in VLDB Journal, 2006
·
Matteo Magnani, Danilo Montesi, “A model for imperfect XML data based on Dempster-Shafer’s theory of evidence”, Technical Report
UBLCS-2005-19,
·
Wenzhong
Zhao, Alex Dekhtyar, Judy Goldsmith, “A Framework for
Management of Semistructured Probabilistic Data,” in Journal of Intelligent Information Systems,
2005.
·
Matteo Magnani, Danilo Montesi, "Dimensions of Ignorance in a Semi-Structured
Data Model", in Proceedings of the
Database and Expert Systems Applications, 15th International Workshop on
(DEXA'04), pages: 933-937, 2004.
·
Wenzhong
Zhao, Alex Dekhtyar, Judy Goldsmith, “Databases for
Interval Probabilities”, in the International Journal of Intelligent Systems
(IJIS), Vol. 19, No. 9, pp 789-815, 2004.
·
Wenzhong
Zhao, Alex Dekhtyar, Judy Goldsmith, “Query Algebra
Operations for Interval Probabilities”, in Proceedings
of 2003 International Conference on Database and Expert Systems Applications
(DEXA), Prague, Czech Republic, pp. 527-536.
·
Judy Goldsmith, Alex Dekhtyar,
Wenzhong Zhao, “Can Probabilistic Databases Help
Elect Qualified Officials?” in Proceedings
of 2003
·
Wenzhong
Zhao, Alex Dekhtyar, Judy Goldsmith, “Representing
Probabilistic Information in XML”, University of Kentucky Department of
Computer Science Tech. Report 770-03 April, 2003.
16. Edward
Hung, David W. Cheung, Ben Kao, Y.L. Liang, "An
Optimization Problem in Data Cube System Design", in
the Proceedings of the Fourth
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2000),
Kyoto, Japan, April 18-20, 2000 (Lecture Notes in Artificial Intelligence 1805:
74-85, 2000). (acceptance rate = 34/116 = 29%)
Cited by:
·
Wo-Shun
Luk, Chao Li, “A Partial Pre-aggregation Scheme for
HOLAP Engines”, in DaWaK (Data Warehousing and Knowledge Discovery)
2004, LNCS 3181: pp. 129-137, 2004
·
C.C. Fabris
and A.A. Freitas “Incorporating deviation-detection
functionality into the OLAP paradigm”, in Proc.
XVI Brazilian Symp. on
Databases (SBBD-2001), pp. 274-285,
17. Edward
Hung, David W. Cheung, "Parallel
Algorithm for Mining Outliers in Large Database", in Heterogeneous and Internet Databases, the
Proceedings of the Ninth International Database Conference (IDC'99),
Hong Kong, pages 184-198, July 15-17, 1999.
Cited by:
·
Yufeng Kou,
Chang-Tien Lu, S. Sirwongwattana,
Yo-Ping Huang, "Survey of fraud detection
techniques", in Proc. of IEEE
International Conference on Networking, Sensing and Control, Vol 2, pages 749-754, 2004
·
Michael Klein, “Eine
Pipelining-Algebra für die effiziente
Anfragebearbeitung im KDD-Prozess” (thesis in German; A pipelining algebra for
efficient query processing within the KDD process)
Book Chapter
·
I. Ceaparu, D.
Demner, E. Hung, H. Zhao, B. Shneiderman,
"'In
Web We Trust': Establishing Strategic Trust Among
Online Customers", in R. Rust and
P.K. Kannan (Editors), E-Service: New Directions in Theory and Practice, M. E. Sharpe
Publishers,
Cited by:
·
L. Patricio, R.P. Fisk, J.F. Cunha, , "Improving satisfaction with bank service
offerings: measuring the contribution of each delivery channel", in Managing Service Quality, Vol. 13 No.6,
pp.471-82, 2003.
Ph.D Dissertation
· Edward
Hung, "Managing Uncertainty and Ontologies in
Databases”, the University of
M.Phil. Thesis
· Edward
Hung, "Data Cube System Design: An Optimization Problem", the
Technical Reports
1.
Edward Hung, Yu Deng, V.S. Subrahmanian, "Maintaining
RDF Views", Technical Report CS-TR-4612. Computer Science Department,
2. Edward
Hung, Yu Deng, V.S. Subrahmanian, "RDF Aggregate Queries and
Views", Technical Report CS-TR-4611. Computer
Science Department,
3. Edward Hung, "ProbSem:
A Probabilistic Semistructured Database Model",
Technical Report, M.S. Scholar paper,
Cited by:
·
M. van Keulen,
A. de Keijzer, W. Alink, “A
probabilistic XML approach to data integration”, in the Proceedings of the International Conference on Data Engineering,
ICDE 2005, April 2005.
4. Edward Hung, "Testing of Database
Applications", individual research project report, Dec 2001.
5. Edward Hung, "Comparative Evaluation of Methods
in Induction of Procmail Recipes from Classified
Emails", individual research project report, Nov 2001.
6. Edward Hung, "Deduction of Procmail
Recipes from Classified Emails", individual research project report, May
2001.
Cited by:
·
Bryan Klimt, Yiming Yang, “The Enron Corpus: A New Dataset for Email
Classification Research”, in the
Proceedings of European Conference on Machine Learning,
7. Edward Hung, "Inapproximability
of Materialized View Selection Problem and Non-metric K-medians Problem",
individual research project report, May 2001.
8. I. Ceaparu, D. Demner, E. Hung, H. Zhao, "'In Web We Trust':
Establishing Strategic Trust Among Online
Customers", group experimental project report, May 2001. Available at http://www.otal.umd.edu/SHORE2001/webTrust/index.html.
9. Edward Hung, "Universal Usability in Practice:
Blind and Low Vision Users", individual project report, April 2001.
Available at http://www.otal.umd.edu/UUPractice/vision.
10. Edward Hung, “Fault Tolerance and Checkpointing Schemes for Clusters of Workstations”,
individual research project report, Dec 1998.
11. Edward Hung, “Parallel Algorithm for Mining Outliers
in Large Databases”, individual research project report, Dec 1998.
12. H.D. Li, E. Hung , Y. Wang,
“Parallel Bitonic Sorting Project Report”, group
programming project report, Dec 1998.
Working Papers
1.
Edward Hung, Yu Deng, V.S. Subrahmanian, "Maintaining RDF Views"