Titlebook: Information Management and Big Data; 4th Annual Internati Juan Antonio Lossio-Ventura,Hugo Alatrista-Salas Conference proceedings 2018 Spri

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Could Machine Learning Improve the Prediction of Child Labor in Peru?,ies need information to correctly allocate their scarce resources to deal with this problem. Although there is research attempting to predict the causes of child labor, previous studies have used only linear statistical models. Non-linear models may improve predictive capacity and thus optimize reso

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Impact of Entity Graphs on Extracting Semantic Relations,ly, relations are extracted based on the lexical and syntactical information at the sentence level. However, global information about known entities has not been explored yet for RE task. In this paper, we propose to extract a graph of entities from the overall corpus and to compute features on this

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Predicting Invariant Nodes in Large Scale Semantic Knowledge Graphs,maintenance and storage. An important subproblem is predicting invariant nodes, that is, nodes within the graph will not have any edges deleted or changed (add-only nodes) or will not have any edges added or changed (del-only nodes). Predicting add-only nodes correctly has practical importance, as s

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独轮车

Purely Synthetic and Domain Independent Consistency-Guaranteed Populations in , precious support to the design of some prototypes. One major challenge of such synthetic data generations is to guarantee the acquisition of sound knowledge bases able to pass the equivalent of a Turing test. That’s why populations have to be restricted to guarantee the consistency until a certain

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土产

混合

Community Detection in Bipartite Network: A Modified Coarsening Approach,tions capable of handling large-scale networks. Multilevel approaches provide a potential solution to scalability, as they reduce the cost of a community detection algorithm by applying it to a coarsened version of the original network. The solution obtained in the small-scale network is then projec

ALLEY

Reconstructing Pedestrian Trajectories from Partial Observations in the Urban Context,tories are low-sampling-rate and, consequently, many movement details are lost. Due to that, trajectory reconstruction techniques aim to infer the missing movement details and reduce uncertainty. Nevertheless, most of the effort has been put into reconstructing vehicle trajectories. Here, we study t