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
Generating non-redundant association rules
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Depth first generation of long patterns
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
A tree projection algorithm for generation of frequent item sets
Journal of Parallel and Distributed Computing - Special issue on high-performance data mining
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A New SQL-like Operator for Mining Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Mining Association Rules from XML Data
DaWaK 2000 Proceedings of the 4th International Conference on Data Warehousing and Knowledge Discovery
Xyleme: A Dynamic Warehouse for XML Data of the Web
IDEAS '01 Proceedings of the International Database Engineering & Applications Symposium
Extracting association rules from XML documents using XQuery
WIDM '03 Proceedings of the 5th ACM international workshop on Web information and data management
Automated xacml policy reconfiguration for evaluation optimisation
Proceedings of the fourth international workshop on Software engineering for secure systems
Knowledge Discovery over the Deep Web, Semantic Web and XML
DASFAA '09 Proceedings of the 14th International Conference on Database Systems for Advanced Applications
Software—Practice & Experience
Knowledge management in sensor enabled online services
FIS'10 Proceedings of the Third future internet conference on Future internet
An efficient algorithm of frequent XML query pattern mining for ebXML applications in e-commerce
Expert Systems with Applications: An International Journal
Efficient incremental breadth-depth XML event mining
Proceedings of the 15th Symposium on International Database Engineering & Applications
Logic-Based association rule mining in XML documents
APWeb'06 Proceedings of the 2006 international conference on Advanced Web and Network Technologies, and Applications
Complex association rules for XML documents
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Positive and negative association rule mining on XML data streams in database as a service concept
Expert Systems with Applications: An International Journal
Web and semantic web query languages: a survey
Proceedings of the First international conference on Reasoning Web
Optimizing queries for web generated sensor data
ADC '11 Proceedings of the Twenty-Second Australasian Database Conference - Volume 115
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In recent years XML has became very popular for representing semistructured data and a standard for data exchange over the web. Mining XML data from the web is becoming increasingly important. Several encouraging attempts at developing methods for mining XML data have been proposed. However, efficiency and simplicity are still a barrier for further development. Normally, pre-processing or post-processing are required for mining XML data, such as transforming the data from XML format to relational format. In this paper, we show that extracting association rules from XML documents without any pre-processing or post-processing using XQuery is possible and analyze the XQuery implementation of the well-known Apriori algorithm. In addition, we suggest features that need to be added into XQuery in order to make the implementation of the Apriori algorithm more efficient.