Titlebook: Information Management and Big Data; 8th Annual Internati Juan Antonio Lossio-Ventura,Jorge Valverde-Rebaza, Conference proceedings 2022 Th

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1865-0929 as a virtual event in December 2021.??.The 25 revised full papers and 2 revised short papers presented were carefully reviewed and selected from 67 submissions. The papers are organized in topical sections on data mining and applications; deep learning and applications; data-driven software enginee

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Hydra: Funding State Prediction for?Kickstarter Technology Projects Using a?Multimodal Deep Learningy projects on Kickstarter. In order to train the model, we created a dataset with 27K Technology projects on Kickstarter between 2009 and 2019. The performance of this proposal reached an AUC value of 93%. Thus, the problem was solved with a different approach that combinates different types of networks to improve results.

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Automatic Data Imputation in?Time Series Processing Using Neural Networks for?Industry and?Medical Dmusic. When we apply them to real-life issues, a common obstacle is the lack of data in intervals within a time series. Usually, to solve it, the missing data is populated with information highly dependent on available datasets, which requires prior analysis. This paper addresses the problem in a no

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Predicting Daily Trends in?the?Lima Stock Exchange General Index Using Economic Indicators and?Finanis work, we investigate machine learning models able to use technical indicators, economic variables, and financial news sentiments to forecast the daily return trend of the S&P/BVL Peru General Index..To the best of our knowledge, no other published S&P/BVL predicting tool considered these joint so

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Government Public Services Presence Index Based on?Open Data in a certain proximity to their homes. Nonetheless, in big cities, some public services are not close enough. To tackle this problem, we propose a methodology to compute a . for measuring how well different zones are in a city are served. We apply our methodology to the city of Lima, showing the ut

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