A collaborative filtering approach to mitigate the new user cold start problem.

The new user cold start issue represents a serious problem in recommender systems as it can lead to the loss of new users who decide to stop using the system due to the lack of accuracy in the recommenda- tions received in that first stage in which they have not yet cast a significant number of votes with which to feed the recommender system?s collaborative filtering core. For this reason it is particularly important to design new similarity metrics which provide greater precision in the results offered to users who have cast few votes. This paper presents a new similarity measure perfected using optimization based on neu- ral learning, which exceeds the best results obtained with current metrics. The metric has been tested on the Netflix and Movielens databases, obtaining important improvements in the measures of accuracy, precision and recall when applied to new user cold start situations. The paper includes the mathematical formalization describing how to obtain the main quality measures of a recommender system using leave- one-out cross validation.

Management of irrigation frequency and nitrogen fertilization to mitigate GHG and NO emissions from drip-fertigated crops

Drip irrigation combined with split application of fertilizer nitrogen (N) dissolved in the irrigation water (i.e. drip fertigation) is commonly considered best management practice for water and nutrient efficiency. As a consequence, its use is becoming widespread. Some of the main factors (water-filled pore space, NH4+ and NO3−) regulating the emissions of greenhouse gases (i.e. N2O, CO2 and CH4) and NO from agroecosystems can easily be manipulated by drip fertigation without yield penalties. In this study, we tested management options to reduce these emissions in a field experiment with a melon (Cucumis melo L.) crop. Treatments included drip irrigation frequency (weekly/daily) and type of N fertilizer (urea/calcium nitrate) applied by fertigation. Crop yield, environmental parameters, soil mineral N concentrations and fluxes of N2O, NO, CH4 and CO2 were measured during 85 days. Fertigation with urea instead of calcium nitrate increased N2O and NO emissions by a factor of 2.4 and 2.9, respectively (P < 0.005). Daily irrigation reduced NO emissions by 42% (P < 0.005) but increased CO2 emissions by 21% (P < 0.05) compared with weekly irrigation. We found no relation between irrigation frequency and N2O emissions. Based on yield-scaled Global Warming Potential as well as NO cumulative emissions, we conclude that weekly fertigation with a NO3−-based fertilizer is the best option to combine agronomic productivity with environmental sustainability. Our study shows that adequate management of drip fertigation, while contributing to the attainment of water and food security, may provide an opportunity for climate change mitigation.