Abstract
Dyreson and Snodgrass as well as Dekhtyar et. al. have provided a probabilistic model (as well as compelling example applications) for why there may be temporal indeterminacy in databases. In this paper, we first propose a formal model for aggregate computation in such databases when there is uncertainty not just in the temporal attribute, but also in the ordinary (non-temporal) attributes. We identify two types of aggregates: event correlated aggregates, and non event correlated aggregations, and provide efficient algorithms for both of them. We prove that our algorithms are correct, and we present experimental results showing that the algorithms work well in practice.
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References
Dyreson, C.E., Snodgrass, R.T.: Supporting valid-time indeterminacy. ACM Trans. Database Syst. 23, 1–57 (1998)
Dekhtyar, A., Ross, R., Subrahmanian, V.S.: Probabilistic temporal databases, I: algebra. ACM Trans. Database Syst. 26, 41–95 (2001)
Wilkinson, N.: Managerial Economics: A Problem-Solving Approach. Cambridge University Press, Cambridge (2005)
Ross, S.M.: A first course on probability. Prentice Hall College Div. Englewood Cliffs (1997)
Lakshmanan, L.V.S., Leone, N., Ross, R., Subrahmanian, V.S.: Probview: a flexible probabilistic database system. ACM Trans. Database Syst. 22, 419–469 (1997)
Lakshmanan, L.V.S., Shiri, N.: A parametric approach to deductive databases with uncertainty. IEEE Transactions on Knowledge and Data Engineering 13, 554–570 (2001)
Wolfram, C.D.: Strategic bidding in a multi-unit auction: An empirical analysis of bids to supply electricity. RAND Journal of Economics 29(4), 703–772 (1998)
Lakshmanan, L.V.S., Shiri, N.: A parametric approach to deductive databases with uncertainty. Knowledge and Data Engineering 13, 554–570 (2001)
Yang, J., Widom, J.: Incremental computation and maintenance of temporal aggregates. The VLDB Journal 12, 262–283 (2003)
Gendrano, J.A.G., Huang, B.C., Rodrigue, J.M., Moon, B., Snodgrass, R.T.: Parallel algorithms for computing temporal aggregates. In: ICDE 1999, pp. 418–427 (1999)
Zhang, D., Markowetz, A., Tsotras, V.J., Gunopulos, D., Seeger, B.: Efficient computation of temporal aggregates with range predicates. In: Symposium on Principles of Database Systems (2001)
Ross, R., Subrahmanian, V.S., Grant, J.: Aggregate operators in probabilistic databases. J. ACM 52, 54–101 (2005)
Baral, C., Tran, N., Tuan, L.: Reasoning about actions in a probabilistic setting. In: Proc. of AAAI 2002, Edmonton, Alberta, Canada, pp. 507–512. AAAI Press, Stanford (2002)
Dean, T., Kanazawa, K.: Probabilistic Temporal Reasoning. In: Proceedings AAAI, St. Paul, MN, USA, pp. 524–529. AAAI Press / The MIT Press (1988)
Dubois, D., Prade, H.: Processing Fuzzy Temporal Knowledge. IEEE Transactions on Systems, Man and Cybernetics 19, 729–744 (1989)
Lehmann, D., Shelah, S.: Reasoning with time and chance. Information and Control 53, 165–198 (1982)
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Udrea, O., Majkić, Z., Subrahmanian, V.S. (2007). Aggregates in Generalized Temporally Indeterminate Databases. In: Prade, H., Subrahmanian, V.S. (eds) Scalable Uncertainty Management. SUM 2007. Lecture Notes in Computer Science(), vol 4772. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75410-7_13
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DOI: https://doi.org/10.1007/978-3-540-75410-7_13
Publisher Name: Springer, Berlin, Heidelberg
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