Link prediction with node clustering coefficient
نویسندگان
چکیده
منابع مشابه
Efficient Link Prediction with Node Clustering Coefficient
Predicting missing links in incomplete complex networks efficiently and accurately is still a challenging problem. The recently proposed CAR (Cannistrai-Alanis-Ravai) index shows the power of local link/triangle information in improving link-prediction accuracy. With the information of level-2 links, which are links between common-neighbors, most classical similarity indices can be improved. Ne...
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In the study of social network evolution, one of the central tasks is link prediction. It aims at inferring new links among existing nodes for the future. Link prediction has many real world applications, including recommending new items in various networks (e.g., friends in Facebook, co-authors in CiteSeerX, products in Amazon), monitoring and preventing criminal activities in a criminal netwo...
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Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various technics. We can note that clustering information plays an important role in s...
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Link prediction has been widely used to extract missing information, identify spurious interactions, evaluate network evolving mechanisms, and so on. In this context, similaritybased algorithms have become the mainstream. However, most of them take into account the contributions of each common neighbor equally to the connection likelihood of two nodes. This paper proposes a model for link predi...
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ژورنال
عنوان ژورنال: Physica A: Statistical Mechanics and its Applications
سال: 2016
ISSN: 0378-4371
DOI: 10.1016/j.physa.2016.01.038