Decision-Guidance Management Systems (DGMS): Seamless integration of data acquisition, learning, prediction, and optimization

Proceedings of the Annual Hawaii International Conference on System Sciences

Volumn , Issue , 2008, Pages

  Brodsky, Alexander ^a,b   Sean Wang, X ^c  

^a George Mason University   (United States)

^b Adaptive Decisions Inc   (United States)

^c University of Vermont   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER ANALYSIS; COMPUTER NETWORKS; EDUCATION; FORECASTING; GALERKIN METHODS; MANAGEMENT; MATHEMATICAL MODELS; MERGERS AND ACQUISITIONS; OPTIMIZATION; PROBABILITY; QUERY LANGUAGES; QUERY PROCESSING; RANDOM ERRORS; RANDOM PROCESSES; RANDOM VARIABLES; SET THEORY;

DATA MODELLING; INTERNATIONAL CONFERENCES; MANAGEMENT SYSTEMS;

PROBABILITY DISTRIBUTIONS;

EID: 51449104134     PISSN: 15301605     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/HICSS.2008.114     Document Type: Conference Paper

References (38)

1. Marcelo A. T. Aragão and Alvaro A. A. Fernandes. Combined inference databases, technical report (version 1.0.0). The University of Manchester, June 2004.
2. Marcelo A. T. Aragão and Alvaro A. A. Fernandes. Seamlessly supporting combined knowledge discovery and query answering: A case study. In Einoshin Suzuki and Setsuo Arikawa, editors, Discovery Science, volume 3245 of Lecture Notes in Computer Science, pages 403-411. Springer, 2004.
3. D. Barbara, H. Garcia-Molina, and D. Porter. The management of probabilistic data. IEEE Transactions on Knowledge and Data Engineering, 4(5):487-50, October 1992.
4. G. Belvaux and L.A. Wolsey. BC-prod: A specialized branch-and-cut system for lot-sizing problems. Management Science, 46:724-738, 2000.
5. Ronald F. Boisvert, Sally E. Howe, and David K. Kahaner. Gams: a framework for the management of scientific software. ACM Trans. Math. Softw., 11(4):313-355, 1985.
6. Alexander Brodsky, Carlotta Domeniconi, and David Etter. Regression databases: Probabilistic querying using sparse learning sets. In Proc. the Fifth International Conference on Machine Learning and Applications (ICMLA'06), 2006.
7. Alexander Brodsky and Hadon Nash. CoJava: Optimization modeling by nondeterministic simulation. In Frédéric Benhamou, editor, CP, volume 4204 of Lecture Notes in Computer Science, pages 91-106. Springer, 2006.
8. Y. Caseau, F.X. Josset, and F. Laburthe. CLAIRE: combining sets, search and rules to better express algorithms. Theory and Practice of Logic Programming, 2(06):769-805, 2002.
9. R. Cavallo and M. Pittarelli. The theory of probabilistic databases. In Proc. Int'l. Conf. on Very Large Data Bases, page 71, Brighton, England, August 1987.
10. Surajit Chaudhuri. Data mining and database systems: Where is the intersection? IEEE Data Eng. Bull, 21(1):4-8, 1998.
11. Reynold Cheng, Yuni Xia, Sunil Prabhakar, Rahul Shah, and Jeffrey Scott Vitter. Efficient indexing methods for probabilistic threshold queries over uncertain data. In VLDB, pages 876-887. Morgan Kaufmann, 2004.
12. Ole-Johan Dahl and Kristen Nygaard. Simula: an algol-based simulation language. Commun. ACM, 9(9):671-678, 1966.
13. Nilesh N. Dalvi and Dan Suciu. Efficient query evaluation on probabilistic databases. In VLDB, pages 864-875. Morgan Kaufmann, 2004.
14. Debabrata Dey and Sumit Sarkar. A probabilistic relational model and algebra. ACM Transactions on Database Systems, 21(3):339-369, September 1996.
15. Thomas Eiter, Thomas Lukasiewicz, and Michael Walter. A data model and algebra for probabilistic complex values. Ann. Math. Artif. Intell, 33(2-4):205-252, 2001.
16. R. Fourer, D. M. Gay, and B. W. Kernighan. A modeling language for mathematical programming. Manage. Sci., 36(5):519-554, 1990.
17. Peter Fritzson and Vadim Engelson. Modelica - a unified object-oriented language for system modelling and simulation. In ECCOP '98: Proceedings of the 12th European Conference on Object-Oriented Programming, pages 67-90, London, UK, 1998. Springer-Verlag.
18. Fuhr, Norbert. A probabilistic relational model for the integration of IR and databases. In Proceedings of the Sixteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, DBMS/IR Integration, pages 309-317, 1993.
19. Lise Getoor and John Grant. PRL: A probabilistic relational language. Machine Learning, 62(1-2):7-31, 2006.
20. J. Han, Y. Fu, K. Koperski, W. Wang, and O. Zaiane. DMQL: A data mining query language for relational databases. In 1996 SIGMOD'96 Workshop. on Research Issues on Data Mining and Knowledge Discovery (DMKD'96), Montreal, Canada, 1996.
21. Jiawei Han and Micheline Kamber. Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers, San Francisco, 2001.
22. Pascal Van Hentenryck, Laurent Michel, Laurent Perron, and Jean-Charles Régin. Constraint programming in OPL. In Gopalan Nadathur, editor, PPDP, volume 1702 of Lecture Notes in Computer Science, pages 98-116. Springer, 1999.
23. Wen-Chi Hon, Zhongyang Zhang, and Nong Zhou. Statistical inference of unknown attribute values in databases. In Bharat Bhargava, Timothy Finin, and Yelena Yesha, editors, Proceedings of the 2nd International Conference on Information and Knowledge Management, pages 21-30, New York, NY, USA, November 1993. ACM Press.
24. Wen-Chi Hou and Zhongyang Zhang. Enhancing database correctness: a statistical approach. In Michael J. Carey and Donovan A. Schneider, editors, Proceedings of the 1995 ACM SIGMOD International Conference on Management of Data, pages 223-232, San Jose, California, 22-25 May 1995.
25. J. Jaffar and J.-L. Lassez. Constraint logic programming. In POPL '87: Proceedings of the 14th ACM SIGACT-SIGPLAN symposium on Principles of programming languages, pages 111-119, New York, NY, USA, 1987. ACM Press.
26. Hasan M. Jamil. Ad hoc association rule mining as SQL3 queries. In Nick Cercone, Tsau Young Lin, and Xindong Wu, editors, ICDM, pages 609-612. IEEE Computer Society, 2001.
27. Jean-Francois Puget and Michel Leconte. Beyond the glass box: Constraints as objects. In International Logic Programming Symposium, pages 513-527, 1995.
28. Maytal Saar-Tsechansky and F. Provost. Active learning for decision-making. Working paper (CeDER-04-06, Stern School of Business, New York University), 2006.
29. Anish Das Sarma, Omar Benjelloun, Alon Y. Halevy, and Jennifer Widom. Working models for uncertain data. In ICDE. IEEE Computer Society, 2006.
30. Oleg Seleznjev and Bernhard Thalheim. Joining multiple random tables. http://www.matstat.umu.se/personal/Oleg/personal/JoinVariability2_1.pdf, 2006.
31. David Simchi-Levi, Xin Chen, and Julien Bramel. The Logic of Logistics: Theory, Algorithms and Applications for Logistics and Supply Chain Management. Springer, Series in Operations Research and, 1997.
32. G. Smolka, M. Henz, and J. Wurtz. Object-oriented concurrent constraint programming in Oz. Principles and Practice of Constraint Programming, pages 29-48, 1995.
33. Sridhar Tayur, Ram Ganeshan, and Michael Magazine (Eds.). Quantitative Models for Supply Chain Management. Kluwer, International Series on Operations Research and Management Science, 1998.
34. Timothy Thomasma and James Madsen. Object oriented programming languages for developing simulation-related software. In WSC' 90: Proceedings of the 22nd conference on Winter simulation, pages 482-485, Piscataway, NJ, USA, 1990. IEEE Press.
35. Octavian Udrea, Yu Deng, Edward Hung, and V. S. Subrahmanian. Probabilistic ontologies and relational databases. In OTM Conferences (1), volume 3760 of Lecture Notes in Computer Science, pages 1-17. Springer, 2005.
36. S. Voss and D.L. Woodruff. Introduction to Computational Optimization Models for Production Planning in a Supply Chain (2nd Edition). Springer, 2006.
37. M. Wallace, S. Novello, and J. Schimpf. ECLiPSe: A platform for constraint logic programming. ICL Systems Journal, 12(1):159-200, 1997.
38. Haixun Wang and Carlo Zaniolo. ATLaS: A native extension of SQL for data mining. In Daniel Barbará and Chandrika Kamath, editors, SDM. SIAM, 2003.