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Data mining has recently drawn a lot of interests as an effective way of generating a concept map in an adaptive learning system that provides students with the personalized learning guidance. Even with significant progresses witnessed in this field, the data mining-based concept map generation needs further improvement both in accuracy and complexity before it can be employed in actual education services. This paper proposes a classification-based approach to significantly reduce computational complexity of concept map generation while maintaining the accuracy of the generated concept map, and demonstrates through simulations that the approach accomplishes the objectives.

This paper proposes a new method for real time implementation of rate-distortion optimized coding mode selection which can be eficiently applied to H. 263-compatible video codecs and other codecs of similar type. W e use our previously proposed normalized rate-distortion model [I] to eficiently compute the rate and the distortion when encoding motion-compensated prediction error signals, instead of actually performing D C T , quantization and entropy-encoding. W e also propose a fast algorithm to find sub-optimal values of coding parameters such as the quantization parameter and the Lagrangian multiplier, A, f o r the trellis search.Experiments show that the proposed scheme provides very good rate control as well as good picture quality, especially when applied to very low bitrate video coding. 0-8186-8821-1/98 $10.00 0 1998 IEEE