Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Communications of the ACM
Designing Web Usability: The Practice of Simplicity
Designing Web Usability: The Practice of Simplicity
Managing Information Quality
Report on the Dagstuhl Seminar
ACM SIGMOD Record
Building large-scale Bayesian networks
The Knowledge Engineering Review
Data quality assessment from the user's perspective
Proceedings of the 2004 international workshop on Information quality in information systems
Defining a data quality model for web portals
WISE'06 Proceedings of the 7th international conference on Web Information Systems
Modeling web-based applications quality: a probabilistic approach
WISE'06 Proceedings of the 7th international conference on Web Information Systems
Effective use of ontologies in software measurement
The Knowledge Engineering Review
A core quality model for web applications
Journal of Web Engineering
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PDQM is a web portal data quality model. This model is centered on the data consumer perspective and for its construction we have developed a process which is divided into two parts. In the first part we defined the theoretical version of PDQM and as a result a set of 33 data quality attributes that can be used to evaluate the data quality in portals were identified. The second part consisted of the conversion of PDQM into an operational model. For this, we adopted a probabilistic approach by using Bayesian networks. In this paper, we show the development of this second part, which was divided into four phases: (1) Definition of a criterion to organize the PDQM's attributes, (2) Generation of a Bayesian network to represent PDQM, (3) Definition of measures and the node probability tables for the Bayesian network and (4) The validation of PDQM.