This paper addresses the author disambiguation problem in academic social network, namely, resolves the phenomenon of synonym problem "multiple names refer to one person" and polysemy problem "one name ...
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The idea that with the help of proper dimensionality reduction, trying to make the samples with the same label be compact and the ones with the different labels be separate after projection, is introduced into classif...
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ISBN:
(纸本)9781479914821
The idea that with the help of proper dimensionality reduction, trying to make the samples with the same label be compact and the ones with the different labels be separate after projection, is introduced into classification problems with high-dimensional data. Based on the analysis of the drawbacks of Discriminant Neighborhood Embedding (DNE) and Locality-Based Discriminant Neighborhood Embedding (LDNE), being the two relatively successful Locally Discriminant Analysis methods proposed in recent years, this paper proposes a method called Similarity-balanced Discriminant Neighborhood Embedding (SBDNE). When constructing the adjacent graph, SBDNE fully takes into account the geometric construction of manifold and the problem of imbalance between the intra-class points and the inter-class points. By endowing these two kinds of samples with different similarities and selecting the near neighbors according to the similarity matrix, not only the structure in the original space can be preserved more efficiently, but also the choice of discriminative information increases. The method proposed here has a better recognition with comparisons to some classical methods, which fully shows that SBDNE method has the capacity to efficiently solve the classification problem.
This paper proposes a new program on the integrity of the data to the probabilistic methods when the number of documents inserted the pseudo-tuple becomes large. In this program, pseudo-tuple inserted in accordance wi...
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Mining frequent itemsets from traditional database is an important research topic in data mining and researchers achieved tremendous progress in this field. However, with the emergence of new applications, the traditi...
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Latent Dirichlet allocation(LDA) is a popular and unsupervised tool for reducing dimension, has been applied in text mining and information retrieval. Belief propagation is competitive in both speed and accuracy compa...
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This paper studies the characteristics of cloud computing environment, based on the traditional access control management technology, proposes a reference model for access control management in the cloud computing, de...
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Studying of image enhancement shows that the quality of image heavily relies on human visual system. In this paper, we apply this fact to design a new image enhancement method for medical images that improves the deta...
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Coding practice is the most efficient way in learning of programming related courses. In this paper, we propose a programming related courses' E-learning platform based on online judge. This platform is designed a...
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For mining useful data from mass data generated by Internet of things, analyses shortages of the traditional Apriori algorithm which has a lower mining efficiency and occupies the larger memory space. So, MapReduce mo...
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While TRIZ is increasingly developing both in research and education, users always encounter difficulties in their attempts to practice it, especially for one of the most complicated inventive problem solving tools, t...
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While TRIZ is increasingly developing both in research and education, users always encounter difficulties in their attempts to practice it, especially for one of the most complicated inventive problem solving tools, the Su-Field analysis, which is used to analyze and improve the efficiency of a technical system. Generally, the process of using a Su-Field model to solve a specific inventive problem includes: building a Problem Model, mapping it to a Generic Problem Model, finding a Generic Solution Model based on the corresponding inventive standard and finally establishing and interpreting a Solution Model in real life. As one of the most important phases of the Su-Field analysis, the last step is normally implemented manually with the help of the pointers to physical effects, which link generic technical functions to specific applications and systems. The adequate pointer, compatible with the context of the specific problem, should be chosen to assist the users to instantiate the Solution Model. However, the pointers to physical effects and the specific problems are built at different levels of abstraction, so it is difficult for the users to choose among many eligible pointers to physical effects given a certain function. This paper proposes a heuristic method to use the pointers to physical effects based on ontology reasoning. The use of formal models, called ontologies, allows to formally define the concepts about the models and the effects and to apply logical reasoning on them. An inventive standards ontology and a physical effects ontology are firstly built to describe the process of Su- Field analysis, and then the logical reasoning rules are established according to a lexical dictionary, the analysis of the inventive standards and the physical effects. The lexical dictionary, based on WordNet, is built to improve the selection of the appropriate effect to apply. Finally, ontology reasoning is implemented to provide heuristic physical effects for the users.
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