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Graph-based ranking has been extensively studied and frequently applied in many applications, such as webpage ranking. It aims at mining potentially valuable information from the raw graph-structured data. Recently, with the proliferation of rich heterogeneous information (e.g., node/edge features and prior knowledge) available in many real-world graphs, how to effectively and efficiently leverage...
Through the collection of lots of relating literatures and analysis of over 6000 actual poisoning cases, this paper established a poisoning features model (living) and autopsy findings model (died) to describe the regularities and differences on the poisoning symptoms caused by different poisons. Based on the two models and combined with the application of the data mining technology the poison can...
The effects of metallic ion (Al, Ti, or La) doping in HfO2 or ZrO2 on the behaviors of oxygen vacancies (V0) such as the formation energy, density of states, and migration energy were investigated by using first principles calculations. The calculations show that, 1) the doping causes an upward shift of deep V0 levels; 2) dopant radius has a weak impact on the relaxed formation energy of V0 (Ejv)...
Recently, Blind Source Separate (BSS) technique has been extended to digital watermarking field. Slowly Feature Analysis (SFA)-a kind of BSS technique-is a new unsupervised learning algorithm to learn nonlinear functions that extract slowly varying signals out of the input data. It expediently can be used to extract image feature and separate the mixed signals. Making use of the advantages of SFA,...
Obtaining invariant representation of time varying signals is one of the major problems in object recognition. Recently, a new method that slowly feature analysis (SFA) which can extract invariant features of temporally varying signals is being explored, which is an extension of independent component analysis (ICA) which has been used for extracting facial feature. The technique of SFA can be extended...
Identifying database corresponding attributes in schema matching plays a key role in data integration in heterogeneous databases. Most of current approaches mainly use schema information of attribute. Little research has attempted to fully explore the use of data content. This paper introduces a novel schema matching algorithm based on data content, which has two-step process. First, through the analysis...
Heterogeneous object co-clustering has become an important research topic in data mining. In early years of this research, people mainly worked on two types of heterogeneous data (denoted by pair-wise co-clustering); while recently more and more attention was paid to multiple types of heterogeneous data (denoted by high- order co-clustering). In this paper, we studied the high- order co-clustering...
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