Diana Hristova_Quantitative Approaches for Modeling Information Quality in Information Systems | Accepted Version Download ( PDF | 26MB) | License: Publishing license for publications excluding print on demand |
Quantitative Approaches for Modeling Information Quality in Information Systems
Hristova, Diana (2016) Quantitative Approaches for Modeling Information Quality in Information Systems. PhD, Universität Regensburg.Date of publication of this fulltext: 22 Mar 2016 13:09
Thesis of the University of Regensburg
Abstract (English)
The dissertation deals with the quantitative measurement of information quality as well as the consideration of the measurement results in decision support, by focusing on the information quality dimensions currency, accuracy, and consistency. The dissertation is based on a theoretical framework, which incorporates the areas of Decision Theory, Knowledge Discovery and Information Quality. ...
The dissertation deals with the quantitative measurement of information quality as well as the consideration of the measurement results in decision support, by focusing on the information quality dimensions currency, accuracy, and consistency. The dissertation is based on a theoretical framework, which incorporates the areas of Decision Theory, Knowledge Discovery and Information Quality. Moreover, uncertainty due to low information quality is modelled by Fuzzy Set Theory and Probability Theory. The dissertation consist of seven papers, which are grouped in four chapters, based on the corresponding information quality dimensions.
Translation of the abstract (German)
Die Dissertation behandelt die quantitative Messung von Informationsqualität und die Berücksichtigung der gemessenen Ergebnisse in Entscheidungen. Dabei liegt der Fokus auf den Informationsqualitätsdimensionen Aktualität, Genauigkeit und Konsistenz. Die Arbeit basiert auf einem theoretischen Rahmenwerk, welches aus den Bereichen der Entscheidungslehre, Knowledge Discovery und Management von ...
Die Dissertation behandelt die quantitative Messung von Informationsqualität und die Berücksichtigung der gemessenen Ergebnisse in Entscheidungen. Dabei liegt der Fokus auf den Informationsqualitätsdimensionen Aktualität, Genauigkeit und Konsistenz. Die Arbeit basiert auf einem theoretischen Rahmenwerk, welches aus den Bereichen der Entscheidungslehre, Knowledge Discovery und Management von Informationsqualität abgeleitet wurde. Dabei werden die Methoden der Wahrscheinlichkeitstheorie und der Fuzzy-Mengenlehre angewendet, um die Unsicherheit aufgrund schlechter Informationsqualität zu modellieren. Die Dissertation besteht aus sieben Papers, die in Abhängigkeit von der behandelten Informationsqualitätsdimension in vier Kapiteln gruppiert sind.
Involved Institutions
Details
| Item type | Thesis of the University of Regensburg (PhD) |
| Open Access Type: | Primary Publication |
|---|---|
| Date | 22 March 2016 |
| Referee | Prof. Dr. Bernd Heinrich |
| Date of exam | 18 December 2015 |
| Institutions | Business, Economics and Information Systems > Institut für Wirtschaftsinformatik > Lehrstuhl für Wirtschaftsinformatik II (Prof. Dr. Bernd Heinrich) Informatics and Data Science > Department Information Systems > Lehrstuhl für Wirtschaftsinformatik II (Prof. Dr. Bernd Heinrich) |
| Keywords | Information quality, currency, Accuracy, Consistency, Metrics, Data mining, Quantitative appropaches |
| Dewey Decimal Classification | 000 Computer science, information & general works > 004 Computer science 300 Social sciences > 330 Economics |
| Status | Published |
| Refereed | Yes, this version has been refereed |
| Created at the University of Regensburg | Yes |
| URN of the UB Regensburg | urn:nbn:de:bvb:355-epub-334105 |
| Item ID | 33410 |
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