Yong-ping Du

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Most classic network entity sorting algorithms are implemented in a homogeneous network, and they are not applicable to a heterogeneous network. Registered patent history data denotes the innovations and the achievements in different research fields. In this paper, we present an iteration algorithm called inventor-ranking, to sort the influences of patent(More)
Rough set theory is an efficient information processing tool used in the discovery of data dependencies. It evaluates the importance of attributes, discovers the patterns of data, reduces all redundant objects and attributes, and seeks the minimum subset of attributes. This paper presents a method for attribute reduction on combination of rough set and(More)
The collaborative filtering (CF) technique has been widely used recently in recommendation systems. It needs historical data to give predictions. However, the data sparsity problem still exists. We propose a new item-based restricted Boltzmann machine (RBM) approach for CF and use the deep multilayer RBM network structure, which alleviates the data sparsity(More)
Information extraction (IE) is the problem of constructing a knowledge base from a corpus of text documents. In recent years, uncertain data applications have grown in importance in the large number of real-world applications, and IE as an uncertain data source. This paper investigated the uncertain data represent and presented a probabilistic framework(More)
One of the main obstacles facing current data mining techniques is attribute reduction. This paper discusses the basic concepts of rough set, and studies two rough approximations operators under neighborhood systems. An attribute reduction method based on rough set theory and neighborhood systems is presented. The experimental results show that the method(More)
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