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The aim of this paper is to investigate the use of oculography signals for the recognition of experts in visual arts. We focused our attention on the number of sight transitions between characteristic image areas (ROIs). In the experiments we used oculographic data recorded at the Department of Experimental Psychology at the Catholic University of Lublin for 29 images and 34 users. The EM method was...
Humans use intuition and experience to classify everything they perceive, but only if the distinguishing patterns are visible. Machine-learning algorithms can learn class information from data sets, but the created classes' meaning isn't always clear. A proposed mixed-initiative approach combines intuitive visualizations with machine learning to tap into the strengths of human and machine classification...
Case retrieval is the most crucial part in CBR. However, traditional case retrieval methods have many disadvantages on accuracy and efficiency. In order to cope with this problem, an improving method based on self-organizing maps (SOM) was proposed in this paper. Firstly, cluster previous cases into several groups using of SOM networks; secondly, input the new case into SOM networks, and identify...
Case retrieval is a central part in Case-based reasoning (CBR), in order to improve accuracy and efficiency of case retrieval, an improving method based on clustering using of self-organizing maps (SOM) was proposed in this paper. The advantage of this method is Cases' visual clustering result provided by SOM networks greatly facilitating retrieval process and decreasing the retrieval time.
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