On Post-Rule Mining of Inductive Rules using a Query Operator

M. Muyeba (UK)


Attributeoriented, rules, query, fuzzy, rule ranking


Most Data Mining applications produce rules that are not used to query the task relevant data but only evaluate their interestingness. Some applications focus on specifying a data mining language for the mining task and do not combine rule querying and database retrieval. Most other applications employ rule querying as a post-data mining operation which merely retrieves the mined rules from a rule base for query optimisation purposes. An inductive technique like Attribute-Oriented Induction (AOI), which drops keys identifying each tuple in the task-relevant data, produces generalised logic rules. An SQL-like operator for performing high-level queries on the original database and the rule base using key-preservation (KP) from AOI KP is presented. Thus a combination of query processing on the database using rules and preserved keys from AOI KP presents a useful and efficient mechanism for understanding the mined rules.

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