Mining for Attribute Definitions in a DistributedTwo-Layered DB System
Journal of Intelligent Information Systems - Special issue on methodologies for intelligent information systems
A Profit-Based Business Model for Evaluating Rule Interestingness
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Tree-based Construction of Low-cost Action Rules
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In papers [4,5], query answering system based on distributed knowledge mining was introduced and investigated. In paper by Ras and Wieczorkowska [3], the notion of an action rule was introduced and for its application domain e-business was taken. In this paper, we generalize the notion of action rules in a similar way to handling global queries in [4,5]. Mainly, when values of attributes for a given customer, used in action rules, can not be easily changed by business user, definitions of these attributes are extracted from other sites of a distributed knowledge system. To be more precise, attributes at every site of a distributed knowledge system are divided into two sets: stable and flexible. Values of flexible attributes, for a given consumer, sometime can be changed and this change can be influenced and controlled by a business user. However, some of these changes (for instance to the attribute "profit") can not be done directly to a chosen attribute. In this case, definitions of such an attribute in terms of other attributes have to be learned. These new definitions are used to construct action rules showing what changes in values of flexible attributes, for a given consumer, are needed in order to re-classify this consumer the way business user wants. But, business user may be either unable or unwilling to proceed with actions leading to such changes. In all such cases we may search for definitions of these flexible attributes looking at either local or remote sites for help.