Detecci\'on de comunidades en redes: Algoritmos y aplicaciones
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.
Sep-14-2020
- Country:
- South America
- North America > United States
- New Jersey (0.04)
- Massachusetts (0.04)
- Kansas (0.04)
- District of Columbia > Washington (0.04)
- Wisconsin > Dane County
- Madison (0.04)
- New York > New York County
- New York City (0.04)
- California > San Francisco County
- San Francisco (0.14)
- Europe
- Spain (0.04)
- United Kingdom > England
- Cambridgeshire > Cambridge (0.14)
- Oxfordshire > Oxford (0.04)
- Cornwall (0.04)
- Netherlands > North Holland
- Amsterdam (0.04)
- Germany
- Berlin (0.04)
- Baden-Württemberg > Karlsruhe Region
- Karlsruhe (0.04)
- Asia
- India (0.04)
- Middle East
- Genre:
- Instructional Material (0.46)
- Research Report (0.40)
- Industry:
- Information Technology (0.46)
- Technology: