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Titlebook: Data Mining and Big Data; 4th International Co Ying Tan,Yuhui Shi Conference proceedings 2019 Springer Nature Singapore Pte Ltd. 2019 artif

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Populations and Their Wellbeingroblem and propose a novel idea using the genetic algorithm to enhance the performance of the system in terms of prediction accuracy, not to mention scalability. Experimental results demonstrated successful performance achievements of the proposed method under various data conditions.
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Conference proceedings 2019d, in July 2019. The 26 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 79 submissions. .They are organized in topical sections named: data analysis; prediction; clustering; classification; mining pattern; mining tasks..
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Colonialism and migration: an overviewn-source data analytical tool which includesd the . model, for an analysis of Bach Chorales. The tools and techniques discussed in this paper have revealed many interesting exploratory fronts such as the semantic analogies of musical concepts which deserve a detailed investigation by computational musicologists.
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https://doi.org/10.1057/9780230118348based on the real big data. From the crawled data, we obtained a set of interesting results, which describes the content-related and writing-related characteristics of online literature content. Our analysis results will shed light on the current status of online literary content and reveal some interesting research topics.
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https://doi.org/10.1057/9781137413079on, and (2) parallel pipeline for a quick response. Extensive experiments using real geospatial datasets show that our algorithm outperforms traditional approaches by an order of magnitude and is superior to the current real-time algorithm for interactive buffer analysis.
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Genetic Testing for Colon Cancerf aligning typical machine learning datasets with open data sources, suggesting useful augmentation options, and the design and implementation of a software tool implementing the approach, available as open-source software.
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Exploring Music21 and Gensim for Music Data Analysis and Visualizationn-source data analytical tool which includesd the . model, for an analysis of Bach Chorales. The tools and techniques discussed in this paper have revealed many interesting exploratory fronts such as the semantic analogies of musical concepts which deserve a detailed investigation by computational musicologists.
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What Are You Reading: A Big Data Analysis of Online Literary Contentbased on the real big data. From the crawled data, we obtained a set of interesting results, which describes the content-related and writing-related characteristics of online literature content. Our analysis results will shed light on the current status of online literary content and reveal some interesting research topics.
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