Machine Learning - special issue on inductive logic programming
GeoMiner: a system prototype for spatial data mining
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
LOF: identifying density-based local outliers
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Efficient algorithms for mining outliers from large data sets
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Outlier detection for high dimensional data
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Discovery of frequent DATALOG patterns
Data Mining and Knowledge Discovery
Scaling Up Inductive Logic Programming by Learning from Interpretations
Data Mining and Knowledge Discovery
Data Mining the Yeast Genome in a Lazy Functional Language
PADL '03 Proceedings of the 5th International Symposium on Practical Aspects of Declarative Languages
Discovery of Spatial Association Rules in Geographic Information Databases
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
Distance-based outliers: algorithms and applications
The VLDB Journal — The International Journal on Very Large Data Bases
A survey of spatial data mining methods databases and statistics point of views
Data warehousing and web engineering
Inducing Multi-Level Association Rules from Multiple Relations
Machine Learning
Spatial associative classification: propositional vs structural approach
Journal of Intelligent Information Systems
Discovery of spatial association rules in geo-referenced census data: A relational mining approach
Intelligent Data Analysis
Outlier detection by logic programming
ACM Transactions on Computational Logic (TOCL)
Mining unexpected multidimensional rules
Proceedings of the ACM tenth international workshop on Data warehousing and OLAP
Mining interesting imperfectly sporadic rules
Knowledge and Information Systems
A Data Mining Methodology for Anomaly Detection in Network Data
KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
A multi-relational approach to spatial classification
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Improving the efficiency of inductive logic programming through the use of query packs
Journal of Artificial Intelligence Research
Efficiently mining regional outliers in spatial data
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
Finding sporadic rules using apriori-inverse
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Assessment of data quality in accounting data with association rules
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Geographical information systems are commonly used for a variety of purposes. Many of them make use of a large database of geographical data, the correctness of which strongly influences the reliability of the system. In this paper, we present an approach to quality maintenance that is based on automatic discovery of non-perfect regularities in the data. The underlying idea is that exceptions to these regularities ('outliers') are considered probable errors in the data, to be investigated by a human expert. A case study shows how the tool can be used for extracting valuable knowledge about outliers in real-world geographical data, in an adaptive manner to the evolving data model supporting it. While the tool aims specifically at geographical information systems, the underlying approach is more broadly applicable for quality maintenance in data-rich intelligent systems.