This thesis is at the intersection of two active esearch areas: Association Rules Mining and Virtual Reality. The main limitations of the association rule extraction algorithms are (i) the large amount of the generated rules and (ii) their low quality. Several solutions have been proposed to address this problem such as, the post-processing of association rules that allows rule validation and extraction of useful knowledge. Whereas rules are automatically extracted by combinatorial algorithms, rule post-processing is done by the user. Visualisation can help the user facing the large amount of rules by representing them in visual form. In order to find relevant knowledge in visual representations, the user needs to interact with these representations. To this aim, it is essential to provide the user with efficient interaction techniques. This work addresses two main issues: an association rule representation that allows the user quickly detection of the most interesting rules and interactive exploration of rules. The first issue requires an intuitive representation metaphor of association rules. The second requires an interactive exploration process allowing the user to explore the rule search space focusing on interesting rules. The main contributions of this work can be summarised as follows: (i) We propose a new classification for Visual Data Mining techniques, based on both 3D representations and interaction techniques. Such a classification helps the user choosing a visual representation and an interaction technique for his/her application. (ii) We propose a new visualisation metaphor for association rules that takes into account the attributes of the rule, the contribution of each one, and their correlations. (iii) We propose a methodology for interactive exploration of associationrules to facilitate the user task facing large sets of rules taking into account his/her cognitive capabilities. In this methodology, local algorithms are used to recommend better rules based on a reference rule which is proposed by the user. Then, the user can both drives extraction and post-processing of rules using appropriate interaction operators. (iv) We developed a tool that implements all the methodology functionality. The tool is based on an intuitive display in a virtual environment and supports multiple interaction methods.
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