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HADI: Mining Radii of Large Graphs
Given large, multimillion-node graphs (e.g., Facebook, Web-crawls, etc.), how do they evolve over time? How are they connected? What are the central nodes and the outliers? In this article we define the Radius plot of a graph and show how it can answer ...
Robust Record Linkage Blocking Using Suffix Arrays and Bloom Filters
Record linkage is an important data integration task that has many practical uses for matching, merging and duplicate removal in large and diverse databases. However, quadratic scalability for the brute force approach of comparing all possible pairs of ...
Temporal Link Prediction Using Matrix and Tensor Factorizations
The data in many disciplines such as social networks, Web analysis, etc. is link-based, and the link structure can be exploited for many different data mining tasks. In this article, we consider the problem of temporal link prediction: Given link data ...
Enhancing Clustering Quality through Landmark-Based Dimensionality Reduction
Scaling up data mining algorithms for data of both high dimensionality and cardinality has been lately recognized as one of the most challenging problems in data mining research. The reason is that typical data mining tasks, such as clustering, cannot ...
Clustering Large Attributed Graphs: A Balance between Structural and Attribute Similarities
Social networks, sensor networks, biological networks, and many other information networks can be modeled as a large graph. Graph vertices represent entities, and graph edges represent their relationships or interactions. In many large graphs, there is ...
Fast Algorithms for Approximating the Singular Value Decomposition
A low-rank approximation to a matrix A is a matrix with significantly smaller rank than A, and which is close to A according to some norm. Many practical applications involving the use of large matrices focus on low-rank approximations. By reducing the ...
