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- W2891231325 abstract "This research explores the ability to extract knowledge about the associations among agricultural products which allows to improve the prediction of future consumption in the local markets of the Andean region of Ecuador. This commercial activity is carried out using Alternative Marketing Circuits (CIALCO), seeking to establish a direct relationship between producer and consumer prices, and promote buying and selling among family groups. The fusion of information from spatially located heterogeneous data sources allows to establish the best association rules between data sources (several products in several local markets) to infer a significant improvement in spatial prediction accuracy for sales future agricultural products." @default.
- W2891231325 created "2018-09-27" @default.
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- W2891231325 date "2018-07-01" @default.
- W2891231325 modified "2023-10-14" @default.
- W2891231325 title "Model Learning and Spatial Data Fusion for Predicting Sales in Local Agricultural Markets" @default.
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- W2891231325 doi "https://doi.org/10.23919/icif.2018.8455594" @default.
- W2891231325 hasPublicationYear "2018" @default.
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