Skip to main content
SpringerLink
Log in

Uncertain Data: Representations, Query Processing, and Applications

  • Chapter
Advances in Probabilistic Databases for Uncertain Information Management

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 304))

Abstract

Uncertain data is common in many emerging applications. In this chapter, we start by surveying a few applications in sensor networks, ubiquitous computing, and scientific databases that require managing uncertain and probabilistic data. We then present two approaches to meeting this requirement. In the first approach, we propose a rich treatment of probability distributions in the system, in particular the SPO framework and the SP-algebra. In the second approach, we stay closer to a traditional DBMS, extended with tuple probabilities or attribute probability distributions, and study the semantics and efficient processing of queries.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Barbará, D., Garcia-Molina, H., Porter, D.: The Management of Probabilistic Data. IEEE Trans. Knowl. Data Eng. 4(5), 487–502 (1992)

    Article  Google Scholar 

  • Benjelloun, O., Das Sarma, A., Halevy, A., Widom, J.: ULDBs: Databases with Uncertainty and Lineage. In: VLDB (2006)

    Google Scholar 

  • Bishop, C.: Pattern Recognition and Machine Learning. Springer (2007)

    Google Scholar 

  • Block, C., Collins, J., Ketter, W.: Agent-based competitive simulation: Exploring future retail energy markets. In: Twelfth International Con-ference on Electronic Commerce, ICEC 2010, pp. 67–76. ACM (August 2010)

    Google Scholar 

  • Brockwell, P., Davis, R.: Introduction to Time Series and Forecasting, 2nd edn. Springer Texts in Statistics (2002)

    Google Scholar 

  • Burton, P., et al.: Size matters: just how big is BIG? – Quanti-fying realistic sample size requirements for human genome epidemiology. International Journal of Epidemiology 38, 263–273 (2009)

    Article  Google Scholar 

  • Cavallo, R., Pittarelli, M.: The Theory of Probabilistic Databases. In: VLDB, pp. 71–9 (1987)

    Google Scholar 

  • de Campos, L.M., Huete, J.F., Moral, S.: Uncertainty Management Using Probability Intervals. In: Proc. International Conference on Information Processing and Management of Uncertainty (IPMU 1994), pp. 190–199 (1994)

    Google Scholar 

  • Cheng, R., Kalashnikov, D., Prabhakar, S.: Evaluating probabilistic queries over imprecise data. In: SIGMOD (2003)

    Google Scholar 

  • Cheng, R., Singh, S., Prabhakar, S., Shah, R., Vitter, J., Xia, Y.: Efficient Join Processing over Uncertain Data. In: CIKM (2006)

    Google Scholar 

  • Dalvi, N., Suciu, D.: Efficient query evaluation on probabilistic databases. In: VLDB (2004)

    Google Scholar 

  • Dekhtyar, A., Goldsmith, J., Hawkes, S.R.: Semistructured Probalistic Databases. In: Proc. SSDBM, pp. 36–45 (2001)

    Google Scholar 

  • Dekhtyar, A., Ross, R.B., Subrahmanian, V.S.: Probabilistic temporal databases, I: algebra. ACM Trans. Database Syst. 26(1), 41–95 (2001)

    Article  MATH  Google Scholar 

  • Dekhtyar, A., Kevin Mathias, K., Gutti, P.: Structured Que-ries for Semistructured Probabilistic Data. In: Proc. 2nd Twente Data Manage-ment Workshop (TDM), pp. 11–18 (June 2006)

    Google Scholar 

  • Deshpande, A., Guestrin, C., Madden, S., Hellerstein, J.M., Hong, W.: Model-driven data acquisition in sensor networks. In: VLDB (2004)

    Google Scholar 

  • DeWitt, D., Naughton, J., Schneider, D.: An Evaluation of Non-Equijoin Algorithms. In: VLDB (1991)

    Google Scholar 

  • Dey, D., Sarkar, S.: A Probabilistic Relational Model and Algebra. ACM Trans. Database Syst. 21(3), 339–369 (1996)

    Article  Google Scholar 

  • Dong, X., Halevy, A., Yu, C.: Data integration with uncer-tainty. The VLDB Journal (April 2009)

    Google Scholar 

  • Dyreson, C.E., Snodgrass, R.T.: Supporting Valid-Time Indeterminacy. ACM Trans. Database Syst. 23(1), 1–57 (1998)

    Article  Google Scholar 

  • Ge, T.: Join Queries on Uncertain Data: Semantics and Efficient Processing. In: The Proceedings of the IEEE 27th International Conference on Data Engineering (ICDE 2011), Hannover, Germany (April 2011)

    Google Scholar 

  • Ge, T., Li, Z.: Approximate Substring Matching over Uncertain Strings. The Proceedings of the VLDB Endowment (PVLDB Journal) 4(11), 772–782 (2011)

    Google Scholar 

  • Ge, T., Zdonik, S.: Handling Uncertain Data in Array Database Systems. In: Proceedings of the IEEE 24th International Conference on Data Engineering (ICDE 2008), Cancun, Mexico (April 2008)

    Google Scholar 

  • Goldsmith, J., Dekhtyar, A., Zhao, W.: Can Probabilistic Databases Help Elect Qualified Officials? In: Proceedings FLAIRS 2003 Conference, pp. 501–505 (2003)

    Google Scholar 

  • Grimmett, G., Stirzaker, D.: Probability and Random Processes, 3rd edn. Oxford (2001)

    Google Scholar 

  • Halpern, J.: An Analysis of First-order Logic of Probability. Artificial Intelligence 46(3), 311–350 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  • Hung, E., Getoor, L., Subrahmanian, V.S.: PXML: A Probabilistic Semistructured Data Model and Algebra. In: ICDE (2003)

    Google Scholar 

  • Hung, E., Getoor, L., Subrahmanian, V.S.: Probabilistic Interval XML. In: ICDT 2003, pp. 358–374 (2003)

    Google Scholar 

  • Jaffray, J.: Bayesian Updating and Belief Functions. IEEE Trans. on Systems, Man and Cybernetics 22(5), 1144–1152 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  • Jampani, R., Xu, F., Wu, M., Perez, L., Jermaine, C., Haas, P.: MCDB: A Monte Carlo Approach to Managing Uncertain Data. In: SIGMOD (2008)

    Google Scholar 

  • Jestes, J., Li, F., Yan, Z., Yi, K.: Probabilistic String Similarity Joins. In: SIGMOD, pp. 327–338 (2010)

    Google Scholar 

  • Keogh, E., Chakrabarti, K., Mehrotra, S., Pazzani, M.: Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases. In: SIGMOD (2001)

    Google Scholar 

  • Komatsu, K., et al.: Gene expression profiling following constitutive activation of MEK1 and transformation of rat intestinal epithelial cells. Molecular Cancer 5, 63 (2006)

    Article  Google Scholar 

  • Kornatzky, Y., Shimony, S.E.: A Probabilistic Object-Oriented Data Model. Data Knowl. Eng. 12(2), 143–166 (1994)

    Article  Google Scholar 

  • Koudas, N., Sevcik, K.: High Dimensional Similarity Joins: Algorithms and Performance Evaluation. In: TKDE (2000)

    Google Scholar 

  • Lakshmanan, L.V.S., Leone, N., Ross, R.B., Subrahmanian, V.S.: ProbView: A Flexible Probabilistic Database System. ACM Trans. Database Syst. 22(3), 419–469 (1997)

    Article  Google Scholar 

  • Mann, M., Hendrickson, R., Pandey, A.: Analysis of Proteins and Proteomes by Mass Spectrometry. Annu. Rev. Biochem. 70, 437–473 (2001)

    Article  Google Scholar 

  • McDonald, M.: To Build a Better Grid. NY Times. July 28 (2011)

    Google Scholar 

  • Mitzenmacher, M., Upfal, E.: Probability & Computing: Randomized Algorithms and Probabilistic Analysis. Cambridge U. Press (2005)

    Google Scholar 

  • Nierman, A., Jagadish, H. V.: ProTDB: Probabilistic Data in XML. In: VLDB 2002, pp. 646–657 (2002)

    Google Scholar 

  • Nilsson, N.J.: Probabilistic Logic. Artificial Intelligence 28(1), 71–87 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  • Ng, R., Subrahmanian, V.S.: Probabilistic Logic Programming. Inf. Comput. 101(2), 150–201 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  • Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann Publishers (1988)

    Google Scholar 

  • Rosson, E.: Native XML Support for Semistructured Probabilistic Data Management, M.S. Thesis, Department of Computer Science, California Polytechnic State University (May 2008)

    Google Scholar 

  • Szewczyk, R., et al.: An analysis of a large scale habitat monitoring application. In: SenSys (2004)

    Google Scholar 

  • Tatbul, N., Buller, M., Hoyt, R., Mullen, S., Zdonik, S.: Confidence-based Data Management for Personal Area Sensor Networks. In: DMSN (2004)

    Google Scholar 

  • Thiagarajan, A., Ravindranath, L., LaCurts, K., Mad-den, S., Balakrishnan, H., Toledo, S., Eriksson, J.: VTrack: Accurate, Energy-Aware Road Traffic Delay Estimation Using Mobile Phones. In: SenSys (2009)

    Google Scholar 

  • Tran, T., Peng, L., Li, B., Diao, Y., Liu, A.: PODS: A New Model and Processing Algorithms for Uncertain Data Streams. In: SIGMOD (2010)

    Google Scholar 

  • Walley, P.: Statistical Reasoning with Imprecise Probabilities. Chapman and Hall (1991)

    Google Scholar 

  • Weichselberger, K.: The theory of interval-probability as a unifying concept for uncertainty. Int. J. Approx. Reasoning 24(2-3), 149–170 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  • Zhao, W., Dekhtyar, A., Goldsmith, J.: Query algebra operations for interval probabilities. In: Mařík, V., Å tÄ›pánková, O., Retschitzegger, W. (eds.) DEXA 2003. LNCS, vol. 2736, pp. 527–536. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  • Zhao, W., Dekhtyar, A., Goldsmith, J.: Databases for interval probabilities. Int. J. Intell. Syst. 19(9), 789–815 (2004)

    Article  MATH  Google Scholar 

  • Zhao, W., Dekhtyar, A., Goldsmith, J.: A Framework for Management of Semistructured Probabilistic Data. J. Intell. Inf. Syst. 25(3), 293–332 (2005)

    Article  MATH  Google Scholar 

  • Zimányi, E.: Query Evaluation in Probabilistic Relational Databases. Theor. Comput. Sci. 171(1-2), 179–219 (1997)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Massachusetts, Lowell, MA, USA

    Tingjian Ge

  2. California Polytechnic State University, San Luis Obispo, CA, USA

    Alex Dekhtyar

  3. University of Kentucky, Lexington, KY, USA

    Judy Goldsmith

Authors
  1. Tingjian Ge
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alex Dekhtyar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Judy Goldsmith
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tingjian Ge .

Editor information

Editors and Affiliations

  1. College of Information Science & Engin., Inst. Computer Applications, Northeastern University, Liaoning, Shenyang, 110004, China, People's Republic

    Zongmin Ma

  2. College of Information Science & Engin., School of Software, Northeastern University, Shenyang, 110004, China, People's Republic

    Li Yan

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Ge, T., Dekhtyar, A., Goldsmith, J. (2013). Uncertain Data: Representations, Query Processing, and Applications. In: Ma, Z., Yan, L. (eds) Advances in Probabilistic Databases for Uncertain Information Management. Studies in Fuzziness and Soft Computing, vol 304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37509-5_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-37509-5_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37508-8

  • Online ISBN: 978-3-642-37509-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation