Handling Uncertainty and Ignorance in Databases: A Rule to Combine Dependent Data

R.S. Choenni, H.E. Blok, Erik Leertouwer

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

8 Citations (Scopus)

Abstract

In many applications, uncertainty and ignorance go hand in hand. Therefore, to deliver database support for effective decision making, an integrated view of uncertainty and ignorance should be taken. So far, most of the efforts attempted to capture uncertainty and ignorance with probability theory. In this paper, we discuss the weakness to capture ignorance with probability theory, and propose an approach inspired by the Dempster-Shafer theory to capture uncertainty and ignorance. Then, we present a rule to combine dependent data that are represented in different relations. Such a rule is required to perform joins in a consistent way. We illustrate that our rule is able to solve the so-called problem of information loss, which was considered as an open problem so far.
Original languageUndefined
Title of host publicationProceedings of the 11th International Conference on Database Systems for Advanced Applications (DASFAA 2006)
EditorsMong Li Lee, Kian-Lee Tan, Vilas Wuwongse
Place of PublicationBerlin, Germany
PublisherSpringer
Pages310-324
Number of pages15
ISBN (Print)978-3-540-33337-1
DOIs
Publication statusPublished - Apr 2006

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume3882
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • METIS-238694
  • IR-63575
  • EWI-7538

Cite this

Choenni, R. S., Blok, H. E., & Leertouwer, E. (2006). Handling Uncertainty and Ignorance in Databases: A Rule to Combine Dependent Data. In M. L. Lee, K-L. Tan, & V. Wuwongse (Eds.), Proceedings of the 11th International Conference on Database Systems for Advanced Applications (DASFAA 2006) (pp. 310-324). [10.1007/11733836_23] (Lecture Notes in Computer Science; Vol. 3882). Berlin, Germany: Springer. https://doi.org/10.1007/11733836_23
Choenni, R.S. ; Blok, H.E. ; Leertouwer, Erik. / Handling Uncertainty and Ignorance in Databases: A Rule to Combine Dependent Data. Proceedings of the 11th International Conference on Database Systems for Advanced Applications (DASFAA 2006). editor / Mong Li Lee ; Kian-Lee Tan ; Vilas Wuwongse. Berlin, Germany : Springer, 2006. pp. 310-324 (Lecture Notes in Computer Science).
@inproceedings{1e11f14bc7ac4e1c86e97b7cab25fefa,
title = "Handling Uncertainty and Ignorance in Databases: A Rule to Combine Dependent Data",
abstract = "In many applications, uncertainty and ignorance go hand in hand. Therefore, to deliver database support for effective decision making, an integrated view of uncertainty and ignorance should be taken. So far, most of the efforts attempted to capture uncertainty and ignorance with probability theory. In this paper, we discuss the weakness to capture ignorance with probability theory, and propose an approach inspired by the Dempster-Shafer theory to capture uncertainty and ignorance. Then, we present a rule to combine dependent data that are represented in different relations. Such a rule is required to perform joins in a consistent way. We illustrate that our rule is able to solve the so-called problem of information loss, which was considered as an open problem so far.",
keywords = "METIS-238694, IR-63575, EWI-7538",
author = "R.S. Choenni and H.E. Blok and Erik Leertouwer",
note = "10.1007/11733836_23",
year = "2006",
month = "4",
doi = "10.1007/11733836_23",
language = "Undefined",
isbn = "978-3-540-33337-1",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "310--324",
editor = "Lee, {Mong Li} and Kian-Lee Tan and Vilas Wuwongse",
booktitle = "Proceedings of the 11th International Conference on Database Systems for Advanced Applications (DASFAA 2006)",

}

Choenni, RS, Blok, HE & Leertouwer, E 2006, Handling Uncertainty and Ignorance in Databases: A Rule to Combine Dependent Data. in ML Lee, K-L Tan & V Wuwongse (eds), Proceedings of the 11th International Conference on Database Systems for Advanced Applications (DASFAA 2006)., 10.1007/11733836_23, Lecture Notes in Computer Science, vol. 3882, Springer, Berlin, Germany, pp. 310-324. https://doi.org/10.1007/11733836_23

Handling Uncertainty and Ignorance in Databases: A Rule to Combine Dependent Data. / Choenni, R.S.; Blok, H.E.; Leertouwer, Erik.

Proceedings of the 11th International Conference on Database Systems for Advanced Applications (DASFAA 2006). ed. / Mong Li Lee; Kian-Lee Tan; Vilas Wuwongse. Berlin, Germany : Springer, 2006. p. 310-324 10.1007/11733836_23 (Lecture Notes in Computer Science; Vol. 3882).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - Handling Uncertainty and Ignorance in Databases: A Rule to Combine Dependent Data

AU - Choenni, R.S.

AU - Blok, H.E.

AU - Leertouwer, Erik

N1 - 10.1007/11733836_23

PY - 2006/4

Y1 - 2006/4

N2 - In many applications, uncertainty and ignorance go hand in hand. Therefore, to deliver database support for effective decision making, an integrated view of uncertainty and ignorance should be taken. So far, most of the efforts attempted to capture uncertainty and ignorance with probability theory. In this paper, we discuss the weakness to capture ignorance with probability theory, and propose an approach inspired by the Dempster-Shafer theory to capture uncertainty and ignorance. Then, we present a rule to combine dependent data that are represented in different relations. Such a rule is required to perform joins in a consistent way. We illustrate that our rule is able to solve the so-called problem of information loss, which was considered as an open problem so far.

AB - In many applications, uncertainty and ignorance go hand in hand. Therefore, to deliver database support for effective decision making, an integrated view of uncertainty and ignorance should be taken. So far, most of the efforts attempted to capture uncertainty and ignorance with probability theory. In this paper, we discuss the weakness to capture ignorance with probability theory, and propose an approach inspired by the Dempster-Shafer theory to capture uncertainty and ignorance. Then, we present a rule to combine dependent data that are represented in different relations. Such a rule is required to perform joins in a consistent way. We illustrate that our rule is able to solve the so-called problem of information loss, which was considered as an open problem so far.

KW - METIS-238694

KW - IR-63575

KW - EWI-7538

U2 - 10.1007/11733836_23

DO - 10.1007/11733836_23

M3 - Conference contribution

SN - 978-3-540-33337-1

T3 - Lecture Notes in Computer Science

SP - 310

EP - 324

BT - Proceedings of the 11th International Conference on Database Systems for Advanced Applications (DASFAA 2006)

A2 - Lee, Mong Li

A2 - Tan, Kian-Lee

A2 - Wuwongse, Vilas

PB - Springer

CY - Berlin, Germany

ER -

Choenni RS, Blok HE, Leertouwer E. Handling Uncertainty and Ignorance in Databases: A Rule to Combine Dependent Data. In Lee ML, Tan K-L, Wuwongse V, editors, Proceedings of the 11th International Conference on Database Systems for Advanced Applications (DASFAA 2006). Berlin, Germany: Springer. 2006. p. 310-324. 10.1007/11733836_23. (Lecture Notes in Computer Science). https://doi.org/10.1007/11733836_23