Mining quantitative association rules in large relational tables
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
GeoMiner: a system prototype for spatial data mining
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Using a Hash-Based Method with Transaction Trimming for Mining Association Rules
IEEE Transactions on Knowledge and Data Engineering
A Survey of Temporal Knowledge Discovery Paradigms and Methods
IEEE Transactions on Knowledge and Data Engineering
CLARANS: A Method for Clustering Objects for Spatial Data Mining
IEEE Transactions on Knowledge and Data Engineering
A Statistical Theory for Quantitative Association Rules
Journal of Intelligent Information Systems
Efficient Mining of Intertransaction Association Rules
IEEE Transactions on Knowledge and Data Engineering
Association Rule Mining on Remotely Sensed Images Using P-trees
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
BIDE: Efficient Mining of Frequent Closed Sequences
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Mining Sequential Patterns by Pattern-Growth: The PrefixSpan Approach
IEEE Transactions on Knowledge and Data Engineering
Discovering Colocation Patterns from Spatial Data Sets: A General Approach
IEEE Transactions on Knowledge and Data Engineering
Mining Sequential Patterns from Multidimensional Sequence Data
IEEE Transactions on Knowledge and Data Engineering
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
A Joinless Approach for Mining Spatial Colocation Patterns
IEEE Transactions on Knowledge and Data Engineering
Extracting spatial semantics in association rules for ocean image retrieval
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Metadata miner assisted integrated information retrieval for Argo ocean data
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
An adaptive knowledge evolution strategy for finding near-optimal solutions of specific problems
Expert Systems with Applications: An International Journal
Mining association rules from time series to explain failures in a hot-dip galvanizing steel line
Computers and Industrial Engineering
A scientific data extraction architecture using classified metadata
The Journal of Supercomputing
Multi-level association rules and directed graphs for spatial data analysis
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
This paper presents an efficient technique for analyzing ARGO ocean data comprising time series of salinity/temperature measurements where informative salinity/temperature patterns are extracted. Most traditional mining techniques focus on finding associations among items within one transaction and are therefore unable to discover rich contextual patterns related to location and time. In order to show the associated salinity/temperature variations among different locations and time intervals, for example, ''if the salinity rose from 0.15psu to 0.25psu in the area that is in the east-northeast direction and is near Taiwan, then the temperature will rise from 0^oC to 1.2^oC in the area that is in the east-northeast direction and is far away from Taiwan next month'', a quantitative inter-transaction association rules mining algorithm is proposed. The FITI and the PrefixSpan algorithms are adopted to maximize the mining efficiency. The strategy is applied to ocean salinity measurements obtained from the waters surrounding Taiwan. These experimental evaluations show that the proposed algorithm achieves better performance than other inter-transaction association rule mining algorithms.