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SIIA Público
SISTEMA INTEGRAL DE INFORMACIÓN ACADÉMICA - PÚBLICO
Título del libro: Global Surface Temperature Model Using Coupled Sugeno Type Fuzzy Inference Systems And Neural Network Optimization Título del capítulo: Term-frequency inverse document frequency for the assessment of similarity in central and state climate change programs: An example for Mexico
Data mining; Inverse problems; Text processing; Extract informations; Level characteristic; Policy assessment; Preliminary approach; Similarity matrix; Term frequency-inverse document frequencies; Text mining; TF-IDF; Climate change
Resumen:
In the present work we present a preliminary approach intended for the assessment of the development of the climate change programs. Particularly we are interested in policies that are develop top-to-bottom by following specific central guidelines. To this end, the numerical statistic "term frequency-inverse document frequency" is used to compare the similarity between the action plans on climate change at national and state level in the case of Mexico. The results allow us to construct a similarity matrix to extract information about how these plans capture local level characteristics and their degree of attachment to the central policy.
