In this paper, we propose an enhanced associative classification method by integrating the dynamic property in the process of associative classification. In the proposed method, we employ a support vector machine（SVM...
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In this paper, we propose an enhanced associative classification method by integrating the dynamic property in the process of associative classification. In the proposed method, we employ a support vector machine（SVM） based method to refine the discovered emerging ~equent patterns for classification rule extension for class lab.l prediction. The empirical study shows that our method can be used to classify increasing resources efficiently and effectively.
With the opinion explosion on Web, there are growing research interests in opinion mining. In this study we focus on an important problem in opinion mining - Aspect Identification (AI), which aims to extract aspect te...
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Recommending related scientific articles for a researcher is very important and useful in practice but also is full of challenges due to the latent complex semantic relations among scientific literatures. To deal with...
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Sharing Semantic Web datasets provided by different publishers in a decentralized environment calls for efficient support from distributed computing technologies. Moreover, we argue that the highly dynamic ad-hoc sett...
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There are a number of leaf recognition methods, but most of them are based on Euclidean space. In this paper, we will introduce a new description of feature for the leaf image recognition, which represents the leaf co...
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Most methods for finding community structure are based on the prior knowledge of network structure type. These methods grouped the communities only when known network is unipartite or bipartite. This paper presents a ...
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We present a hierarchical chunk-to-string translation model, which can be seen as a compromise between the hierarchical phrasebased model and the tree-to-string model, to combine the merits of the two models. With the...
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MicroRNAs(miRNAs)are a class of small non-coding RNAs that play important roles in post-transcriptional regulation of gene expression[1].A large number of miRNAs have been found to be involved in a broad spectrum of b...
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MicroRNAs(miRNAs)are a class of small non-coding RNAs that play important roles in post-transcriptional regulation of gene expression[1].A large number of miRNAs have been found to be involved in a broad spectrum of biological functions such as regulation of innate and adaptive immunity,cell differentiation and development as well as
Complex networks are extensively studied in various areas such as social networks,biological networks,Internet and networks have many characters such as small-diameter,higher cluster and power-law degree ***-world is...
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Complex networks are extensively studied in various areas such as social networks,biological networks,Internet and networks have many characters such as small-diameter,higher cluster and power-law degree ***-world is evolved for efficient information transformation and ***,navigation is an important functional character of *** researches mostly focus on understanding the navigability of small-world networks by analyzing the diameter and the routing *** this paper,we use the navigability to model the basic structural complexity of a *** is,given a network topology,we need a model to evaluate how complex the topology *** network complexity models have been proposed but none of them consider the navigability factor of the network *** believe that using the navigability factor to evaluate the network structural complexity is a feasible and reasonable *** use the adjacent matrix to build a navigation transition matrix and evaluate the randomness of random walks on the transition matrix by defining navigation entropy on *** use the iteration of the random walk matrix to evaluate the navigability of a network and the complexity of *** is,the higher the navigation entropy,the higher the randomness of a *** lower the navigation entropy,the higher the structure of a *** apply the navigation entropy model on a set of structural and random network topologies to show how the model can show the different complexity of networks.
Searching frequent patterns in transactional databases is considered as one of the most important data mining problems and Apriori is one of the typical algorithms for this task. Developing fast and efficient algorith...
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