Gentrification is not always detected at the time by the society, politics, and planning to carry out interventions that mitigate its adverse effects. Its implications are so important in the physiognomy social of cities, which will be relevant to every tool that allows you to predict or evidence of any kind of sign of gentrification.
We propose the realization of a Report on the gentrification in the area of work of the urban action, making the detection of areas linked to processes of gentrification, whether they are emerging or established. To do this, we will use methodologies of extraction of information based on data mining techniques from the sciences of the Artificial Intelligence.
The results will identify profiles urban the state of the art have been attributed to gentrification allowing for the early detection of processes like in the areas themselves and nearby urban interventions to be evaluated.