Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Mining for Strong Negative Associations in a Large Database of Customer Transactions
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Negative Association Rules
ISCC '02 Proceedings of the Seventh International Symposium on Computers and Communications (ISCC'02)
Providing Database as a Service
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Extracting association rules from XML documents using XQuery
WIDM '03 Proceedings of the 5th ACM international workshop on Web information and data management
Mining association rules from XML data using XQuery
ACSW Frontiers '04 Proceedings of the second workshop on Australasian information security, Data Mining and Web Intelligence, and Software Internationalisation - Volume 32
Efficient mining of both positive and negative association rules
ACM Transactions on Information Systems (TOIS)
Mining positive and negative association rules: an approach for confined rules
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Online Mining (Recently) Maximal Frequent Itemsets over Data Streams
RIDE '05 Proceedings of the 15th International Workshop on Research Issues in Data Engineering: Stream Data Mining and Applications
Research issues in data stream association rule mining
ACM SIGMOD Record
StatStream: statistical monitoring of thousands of data streams in real time
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Security in outsourcing of association rule mining
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
A survey on querying encrypted XML documents for databases as a service
ACM SIGMOD Record
Mining frequent itemsets over data streams using efficient window sliding techniques
Expert Systems with Applications: An International Journal
An Effective Algorithm for Mining Positive and Negative Association Rules
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 04
| Hi-index | 12.05 |
In recent years, data mining has become one of the most popular techniques for data owners to determine their strategies. Association rule mining is a data mining approach that is used widely in traditional databases and usually to find the positive association rules. However, there are some other challenging rule mining topics like data stream mining and negative association rule mining. Besides, organizations want to concentrate on their own business and outsource the rest of their work. This approach is named ''database as a service concept'' and provides lots of benefits to data owner, but, at the same time, brings out some security problems. In this paper, a rule mining system has been proposed that provides efficient and secure solution to positive and negative association rule computation on XML data streams in database as a service concept. The system is implemented and several experiments have been done with different synthetic data sets to show the performance and efficiency of the proposed system.