… With the rapid development of information technologies, various big graphs are prevalent in
… find high-quality communities from big graphs is an important research topic in the era of big …

… The cherry on the cake is speed: as we shall see soon, one can perform k local searches
embedded within an iterated local search much faster than if the k local searches are run with …

… may find arbitrarily badly connected communities. In particular, we show that Louvain may
identify communities … That is, one part of such an internally disconnected community can reach …

… However, tasks on disassortative graphs usually require nonlocal aggregation. In addition,
we find that local aggregation is even harmful for some disassortative graphs. In this work, we …

… Namely, we perform an exhaustive search of existing community detection methods for
node-attributed social networks. What is more, we propose a classification of them based on …

… Then, in Step 3, we take out 2 edges and add another 2 at random, and after a local search,
an improved solution is obtained with a value of 39. Continuing in that way, the optimal …

… Furthermore, one needs a local search method. The local search method can use a single
… the result of the shaking step is improved using the local search in line 6. Lines 7–11 check …

… graph to general inhomogeneous random graphs. In Chapter 4, we discuss the local limit and
large … , and in Chapter 5, we discuss the local structure in, and connectivity of, preferential …

… also build or refine the k-NN graph for the datasets we consider, but it has a large memory …
NN graph has been constructed for an image dataset, we can find paths in the graph between …

… The data structure for maintaining shortest paths in large graphs is a well studied field (eg,
[45]) where one approach is the shortest path tree. While the variants of shortest path tree …