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

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發(fā)表于 2025-3-21 18:32:56 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Information Management and Big Data
副標(biāo)題4th Annual Internati
編輯Juan Antonio Lossio-Ventura,Hugo Alatrista-Salas
視頻videohttp://file.papertrans.cn/466/465097/465097.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Information Management and Big Data; 4th Annual Internati Juan Antonio Lossio-Ventura,Hugo Alatrista-Salas Conference proceedings 2018 Spri
描述This book constitutes the refereed proceedings of the?4th Annual International Symposium on Information Management and Big Data, SIMBig 2017, held in Lima, Peru, in September 2017..The?10 revised full papers presented were carefully reviewed and selected from 71 submissions. The papers address issues such as?Data Science, Big Data, Data Mining, Natural Language Processing, Text Mining, Information Retrieval, Machine?Learning, Semantic Web, Ontologies, Web Mining, Knowledge Representation and?Linked Open Data, Social Web and Web Science, Information Visualization..
出版日期Conference proceedings 2018
關(guān)鍵詞Big Data; Text Analytics; Information Retrieval; OLAP and MDA Models; Semantic Web; Linked Data; Text Mini
版次1
doihttps://doi.org/10.1007/978-3-319-90596-9
isbn_softcover978-3-319-90595-2
isbn_ebook978-3-319-90596-9Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer International Publishing AG, part of Springer Nature 2018
The information of publication is updating

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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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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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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
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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
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