Extracting schema from semistructured data
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Storing semistructured data with STORED
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Borders: An Efficient Algorithm for Association Generation in Dynamic Databases
Journal of Intelligent Information Systems
Quantifying the utility of the past in mining large databases
Information Systems
Querying websites using compact skeletons
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
Discovering Structural Association of Semistructured Data
IEEE Transactions on Knowledge and Data Engineering
Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
ICDT '97 Proceedings of the 6th International Conference on Database Theory
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Sampling Large Databases for Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
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Semistructured data arise frequently in the Web or in data integration systems. Semistructured objects describing the same type of information have similar but not identical structure. Finding the common schema of a collection of semistructured objects is a very important task and due to the huge volume of such data encountered, data mining techniques have been employed. Maintenance of the discovered schema in case of updates, i.e., addition of new objects, is also a very important issue. In this paper, we study the problem of maintaining the discovered schema in the case of the addition of new objects. We use the notion of "negative borders" introduced in the context of mining association rules in order to efficiently find the new schema when objects are added to the database. We present experimental results that show the improved efficiency achieved by the proposed algorithm.