A theory of diagnosis from first principles
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Simulation, Knowledge-Based Computing, and Fuzzy Statistics
Simulation, Knowledge-Based Computing, and Fuzzy Statistics
Subjective bayesian methods for rule-based inference systems
AFIPS '76 Proceedings of the June 7-10, 1976, national computer conference and exposition
Class Noise vs. Attribute Noise: A Quantitative Study
Artificial Intelligence Review
Class noise vs. attribute noise: a quantitative study of their impacts
Artificial Intelligence Review
Data Mining and Knowledge Discovery
Evaluating noise elimination techniques for software quality estimation
Intelligent Data Analysis
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
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Identifying inaccurate data has long been regarded as a significant and difficult problem in AI. In this paper, we present a new method for identifying inaccurate data on the basis of qualitative correlations among related data. First, we introduce the definitions of related data and qualitative correlations among related data. Then we put forward a new concept called support coefficient function (SCF). SCF can be used to extract, represent, and calculate qualitative correlations among related data within a dataset. We propose an approach to determining dynamic shift intervals of inaccurate data, and an approach to calculating possibility of identifying inaccurate data, respectively. Both of the approaches are based on SCF. Finally we present an algorithm for identifying inaccurate data by using qualitative correlations among related data as confirmatory or disconfirmatory evidence. We have developed a practical system for interpreting infrared spectra by applying the method, and have fully tested the system against several hundred real spectra. The experimental results show that the method is significantly better than the conventional methods used in many similar systems.