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Data Science
  • Language: en
  • Pages: 668

Data Science

This two volume set (CCIS 1257 and 1258) constitutes the refereed proceedings of the 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020 held in Taiyuan, China, in September 2020. The 98 papers presented in these two volumes were carefully reviewed and selected from 392 submissions. The papers are organized in topical sections: database, machine learning, network, graphic images, system, natural language processing, security, algorithm, application, and education.

Data Science
  • Language: en
  • Pages: 508

Data Science

This two-volume set (CCIS 1879 and 1880) constitutes the refereed proceedings of the 9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023 held in Harbin, China, during September 22–24, 2023. The 52 full papers and 14 short papers presented in these two volumes were carefully reviewed and selected from 244 submissions. The papers are organized in the following topical sections: Part I: Applications of Data Science, Big Data Management and Applications, Big Data Mining and Knowledge Management, Data Visualization, Data-driven Security, Infrastructure for Data Science, Machine Learning for Data Science and Multimedia Data Management and Analysis. Part II: Data-driven Healthcare, Data-driven Smart City/Planet, Social Media and Recommendation Systems and Education using big data, intelligent computing or data mining, etc.

Data Science
  • Language: en
  • Pages: 738

Data Science

This two volume set (CCIS 1257 and 1258) constitutes the refereed proceedings of the 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020 held in Taiyuan, China, in September 2020. The 98 papers presented in these two volumes were carefully reviewed and selected from 392 submissions. The papers are organized in topical sections: database, machine learning, network, graphic images, system, natural language processing, security, algorithm, application, and education. The chapter “Highly Parallel SPARQL Engine for RDF” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Data Science
  • Language: en
  • Pages: 793

Data Science

  • Type: Book
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  • Published: 2017-09-15
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  • Publisher: Springer

This two volume set (CCIS 727 and 728) constitutes the refereed proceedings of the Third International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017 (originally ICYCSEE) held in Changsha, China, in September 2017. The 112 revised full papers presented in these two volumes were carefully reviewed and selected from 987 submissions. The papers cover a wide range of topics related to Basic Theory and Techniques for Data Science including Mathematical Issues in Data Science, Computational Theory for Data Science, Big Data Management and Applications, Data Quality and Data Preparation, Evaluation and Measurement in Data Science, Data Visualization, Big Data Mi...

Data Science
  • Language: en
  • Pages: 520

Data Science

This two volume set (CCIS 1628 and 1629) constitutes the refereed proceedings of the 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022 held in Chengdu, China, in August, 2022. The 65 full papers and 26 short papers presented in these two volumes were carefully reviewed and selected from 261 submissions. The papers are organized in topical sections on: Big Data Management and Applications; Data Security and Privacy; Applications of Data Science; Infrastructure for Data Science; Education Track; Regulatory Technology in Finance.

Data science
  • Language: en
  • Pages: 359

Data science

None

6GN for Future Wireless Networks
  • Language: en
  • Pages: 438

6GN for Future Wireless Networks

None

Machine Learning for Cyber Physical Systems
  • Language: en
  • Pages: 124

Machine Learning for Cyber Physical Systems

  • Type: Book
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  • Published: 2016-02-19
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  • Publisher: Springer

The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Lemgo, October 1-2, 2015. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.

ICIDC 2022
  • Language: en
  • Pages: 2599

ICIDC 2022

The 2022 International Conference on Information Economy, Data Modeling and Cloud Computing (ICIDC 2022) was successfully held in Qingdao, China from June 17 to 19, 2022. Under the impact of COVID-19, ICIDC 2022 was held adopting a combination of online and offline conference. During this conference, we were greatly honored to have Prof Datuk Dr Hj Kasim Hj Md Mansur from Universiti Malaysia Sabah, Malaysia to serve as our Conference Chairman. And there were 260 individuals attending the conference. The conference agenda was composed of keynote speeches, oral presentations, and online Q&A discussion. The proceedings of ICIDC 2022 cover various topics, including Big Data Finance, E-Commerce a...

Data Clustering
  • Language: en
  • Pages: 654

Data Clustering

  • Type: Book
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  • Published: 2016-03-29
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  • Publisher: CRC Press

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabi...