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Heterogeneous graph is a popular data model to represent the real-world relations with abundant semantics. To analyze heterogeneous graphs, an important step is extracting homogeneous graphs from the heterogeneous graphs, called homogeneous graph extraction. In an extracted homogeneous graph, the relation is defined by a line pattern on the heterogeneous graph and the new attribute values of the relation...
Using dictionary atoms to reconstruct input vectors is of great interest in spare representation. However, a key challenge is how to find a proper dictionary. In this paper, we introduce an active dictionary learning (ADL) method which incorporates active learning criteria to select atoms for dictionary construction with the consideration of both classification and reconstruction errors. Specifically,...
Constructing the graphs with some specific properties is an important and interesting problem in the field of graph theory. A graph G is uniquely k-colorable if the chromatic number of G is k and G has only one k-coloring up to permutation of the colors. In this paper, we give three methods for recursively constructing uniquely 3-colorable graphs. Moreover, we give a simple counterexample on 16 vertices...
Analyzing chromatic number in coloring problem is a tough topic in graph analysis. We focus on the basic theory for a particular type of chromatic number. This will give us insights on the basic topological structure guiding lots of networks in the coming trend of big data era. An adjacent vertex-distinguishing total k-coloring is a proper total k-coloring of a graph G such that for any two adjacent...
Researches on the application of sets increasingly attract many scholars, like encryption technique, experimental design, algorithm improving, program design, artificial intelligence, the security of image processing and so on. Given that, studies on set theory seem more necessary. In this paper, we discuss a kind of set named anti-average set, which is derived from the graceful labellings of graphs...
Community structure as a significant feature helps us understand networks in a mesoscopic view. Existing approaches for community detection haven't considered about the formation of communities, whereas community in real social networks is usually established around influential nodes. In this paper, we present an efficient and effective framework based on local influence to detect both overlapping...
Capacity regions and separability results are obtained for several classes of parallel discrete memoryless interference channels with strong interference. In addition, a new class of discrete memoryless interference channels under very strong interference is defined which does not belong to any existing classes.
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