Detección de comunidades en redes: Algoritmos y aplicaciones
This is an incremental work that provides a systematic analysis for researchers in network science and graph theory.
The thesis conducted a review and classification of community detection methods in networks, analyzing their computational complexity and evaluating clustering quality through various measures.
This master's thesis work has the objective of performing an analysis of the methods for detecting communities in networks. As an initial part, I study of the main features of graph theory and communities, as well as common measures in this problem. Subsequently, I was performed a review of the main methods of detecting communities, developing a classification, taking into account its characteristics and computational complexity for the detection of strengths and weaknesses in the methods, as well as later works. Then, study the problem of classification of a clustering method, this in order to evaluate the quality of the communities detected by analyzing different measures. Finally conclusions are elaborated and possible lines of work that can be derived.