An Interactive Tool for Human Active Learning in Constrained Clustering

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This paper describes an interactive tool for constrained clustering that helps users to efficiently select effective constraints during the constrained clustering process. Constrained clustering is a promising technique for smart data aggregation or filtering, which is indispensable for the user activity on the Web. Effective bias is necessary for the constraints selection in order to make it a more practical technique, the authors approach this problem by incorporating human biasing using an easy manipulatable interactive tool. This tool has several functions such as the 2-D visual arrangement of a dataset and constraint assignment by mouse manipulation.