Angelina A. Tzacheva

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Action rules can be seen as an answer to the question: what one can do with results of data mining and knowledge discovery? Some applications include: medical field, e-commerce, market basket analysis , customer satisfaction, and risk analysis. Action rules are logical terms describing knowledge about possible actions associated with objects , which is(More)
In this paper, we give a strategy for constructing all action rules from a given information system and show that action rules constructed by system DEAR, cover only a small part of all action rules. Clearly, we are not interested in all action rules as we are not interested in extracting all possible rules from an information system. Classical strategies(More)
Action rules are built from atomic expressions called atomic action terms and they describe possible transitions of objects from one state to another. They involve changes of values within one decision attribute. Association action rule is similar to an action rule but it may refer to changes of values involving several attributes listed in its decision(More)
At a time when the quantity of music media surrounding us is rapidly increasing and the access to recordings as well as the amount of music files available on the Internet is constantly growing, the problem of building music recommendation systems is of great importance. In this work, we perform a study on automatic classification of musical instruments. We(More)
A new class of rules, called action rules, show what actions should be taken to improve the profitability of customers. Action rules introduced by (Ras and Wieczorkowska, 2000a) and investigated further by (Ras and Gupta, 2002a) assume that attributes in a database are divided into two groups: stable and flexible. These reflect the ability of a business(More)
We present a generalization of a strategy, called SCIKD, proposed in [7] that allows to reduce a disclosure risk of confidential data in an information system S [10] using methods based on knowledge discovery. The method proposed in [7] protects confidential data against Rule-based Chase, the null value imputation algorithm driven by certain rules [2], [4].(More)