M. Muyeba (UK)
Attribute-oriented, 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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