A conceptual framework and belief‐function approach to assessing overall information quality
By Matthew Bovee, R. Srivastava, B. Mak. International Journal of Intelligent Systems, 2003
316 citations recorded by the source corpus.
Subfields: Artificial Intelligence, General Decision Sciences, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/d5eeb278d10af0b4b93c84d0e6fd514b55d894e6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Jens Lehmann
- Sören Auer
- Amrapali Zaveri
- Gerhard Weikum
- Christian Bizer
- Fabian M. Suchanek
- Heiko Paulheim
- Qi Wu
In Management Science and Operations Research
- Jens Lehmann
- Sören Auer
- Jorge Bernardino
- Andrea Maurino
- Seyma Nur Soydemir
- Marco Torchiano
- Nuno Laranjeiro
- Raimondo Iemma
Citations in the corpus
- A Survey on Data Quality: Classifying Poor Data (2015, background): “A conceptual framework and belief function to assess information quality is discussed in [39].”
- Antecedents of Information and System Quality: An Empirical Examination Within the Context of Data Warehousing (2005, unknown): “[ 14 , 39 , 82 ] A cc e s s i b ili t y I n f o r m a t i on c an be ob t a i ned w hen needed .”
- Open data quality measurement framework: Definition and application to Open Government Data (2016, background): “In the literature of data quality, several authors contributed to build an extensive list of data quality characteristics: see for instance Wand and Wang (1996), Wang and Strong (1996), Redman (1996), Jarke et al. (1995), Bovee et al. (2003), Naumann (2002), (Batini & Scannapieco, 2006).”
- Data quality: A survey of data quality dimensions (2012, background): “Volatility is a measure of information instability the frequency of change of the value for an entity attribute [2, 16].”
- Quality assessment for Linked Data: A Survey (2015, background): “Previously published literature provides a thorough classification of the data quality dimensions [11,32,49,52,61,63].”