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Recommender systems benefit people's daily lives at every moment. While considerable attentions have been drawn by performance in one-step recommendation and static user-item network, recommenders' performance on temporally evolving networks remains unclear. To address this issue, this paper firstly adopts a bipartite network to describe the online commercial system. We then propose a network evolution...
There is an urgent need to discover or predict DDIs, which would cause serious adverse drug reactions. However, preclinical detection of DDIs bear high cost. Similarity-based computational approaches can be the assistance of experimental approaches. Utilizing pre-market drug similarities, they are able to predict DDIs on a large scale. However, they neglect the topological structure among DDIs and...
According to the off-line handwritten Chinese characters, a classification and recognition method which is combined by pruning FSVM coarse classification and SVM fine classification is proposed in this text. First cut no value minor to reduce the number of support vector machines, and then determine the coarse classification through fuzzy membership when the coarse classification is done. In fine...
We present a study of discriminative training of classifiers using both maximum mutual information (MMI) and minimum classification error (MCE) criteria for online handwritten Chinese/Japanese character recognition based on continuous-density hidden Markov models. It is observed that MCE-trained classifiers can achieve a much higher recognition accuracy than that of MMI-trained ones. Benchmark results...
Penalized feature selection and classification techniques are promising in bioinformatics studies of high-dimensional microarray data. The penalized objective function of penalization methods includes two parts: classification objective function and penalty terms. We propose a novel L1 + L1 model. The classification objective function is chosen as the negative log-likelihood function based on the...
We present a new feature extraction approach to online Chinese handwriting recognition based on continuous-density hidden Markov models (CDHMM). Given an online handwriting sample, a sequence of time-ordered dominant points are extracted first, which include stroke-endings, points corresponding to local extrema of curvature, and points with a large distance to the chords formed by pairs of previously...
In online handwritten math expression recognition, one-pass dynamic programming can produce high-quality symbol graphs in addition to best symbol sequence hypotheses, especially after discriminative training and trigram graph rescoring. Impact of symbol graphs on whole expression recognition, however, has not been referred to yet, since the interface of structure analysis module does not work well...
Presently the system for recognition of Chinese medical pulse condition mainly aims at single pulse signal; the investigation of compound pulse signal is less. Article mainly researches single pulse signal and compound pulse signal. Firstly, we use wavelet analysis to extract character of pulse signal. Secondly, we make use of the nerve network to recognize. It constructs a considerably practical...
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