Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Toward Multidatabase Mining: Identifying Relevant Databases
IEEE Transactions on Knowledge and Data Engineering
Synthesizing High-Frequency Rules from Different Data Sources
IEEE Transactions on Knowledge and Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Peculiarity Oriented Multidatabase Mining
IEEE Transactions on Knowledge and Data Engineering
Knowledge Discovery in Multiple Databases
Knowledge Discovery in Multiple Databases
Database classification for multi-database mining
Information Systems
Mining Multiple Data Sources: Local Pattern Analysis
Data Mining and Knowledge Discovery
A collaborative filtering framework based on fuzzy association rules and multiple-level similarity
Knowledge and Information Systems
Data quality awareness: a case study for cost optimal association rule mining
Knowledge and Information Systems - Special Issue on Mining Low-Quality Data
Interactive visual exploration of association rules with rule-focusing methodology
Knowledge and Information Systems
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Because of the rapid growth in information and communication technologies, a company’s data may be spread over several continents. For an effective decision-making process, knowledge workers need data, which may be geographically spread in different locations. In such circumstances, multi-database mining plays a major role in the process of extracting knowledge from different data sources. In this paper, we have proposed a new methodology for synthesizing high-frequency rules from different data sources, where data source weight has been calculated on the basis of their transaction population. We have also proposed a new method for calculating global confidence. Our goal in synthesizing local patterns to obtain global patterns is that, the support and confidence of synthesized patterns must be very nearly same if all the databases are integrated and mono-mining has been done. Experiments conducted clearly establish that the proposed method of synthesizing high-frequency rules fairly meets the stipulation.