Task: Paper Review
Input (Spanish, English): Review_1: Este trabajo propone un nuevo enfoque basado en [25] para apoyar la recomendación de los RS mediante la evolución de los pesos de las características de los usuarios a través de dos enfoques de utilización de algoritmos genéticos. El trabajo parece técnicamente correcto y la propuesta presenta resultados robustos de acuerdo a lo presentado en el documento.  El documento posee una serie de errores al parecer tipográficos que inducen a confusión, donde se cambian los nombres de variables, abreviaciones o formato de presentación de variables  subíndices, etc. Por ejemplo: ecuación 2, función w, abreviación CF, figura 3, figura 6. El enfoque aparentemente utiliza solo una parte de la BD por motivos de eficiencia, sería bueno utilizar alguna técnica de indexado para apoyar este proceso. Review_2: This paper aims to show new deployment alternative for recommender systems. To this end, the authors use two variations CHC genetic algorithm.  - It's a good job. - It is clear and very detailed.  - There are inconsistencies in the notation should be improved. The formula (7) has a notation different from the rest of the equations. - On the same point, the figure (3) refers to "perfil", "pesos", "euclidiana" and "vecindad"; these words aren't related with the text. - I think that the results shown in graphs would be more useful if they are shown in tables. Review_3: The paper is well structured. It follows a logical sequence of sections.  The paper does not fix to the Infonor conference template.  The english grammar is poor. It makes the paper difficult to read and follow. Either:  a) rewrite the paper in spanish, or b) make the paper reviewed by a professional traslator  Most of the references are not recent (2005-2010). No new work since 2003? Some references do not indicate year.  Problems with equations, fonts, etc.  Figures 5-17 are not referenced/discussed/explained. It may be better to present these figures as a table.  Both, result analysis and conclusions, declare that GA CHC is better than Pearson´s correlation Algorithm. However, this analysis and conclusion is not supported for a wide variety of situations and conditions. Therefore, a true validation work is missing. 
Output (English): accept