Big Data Analytics in Astronomy, Science, and Engineering: 10th International Conference on Big Data Analytics, BDA 2022, Aizu, Japan, December 5-7, 2022, Proceedings

This book presents the proceedings of the 10th International Conference on Big Data Analytics,BDA 2022,which included 14 full papers on various topics such as big data analytics, networking, social media, search, information extraction, image processing, spatial, text, mobile, and graph data analysis, machine learning, and healthcare.

Format: Paperback / softback
Length: 246 pages
Publication date: 19 March 2023
Publisher: Springer International Publishing AG

The 10th International Conference on Big Data Analytics, BDA 2022, was held in Aizu, Japan, in December 2022, in a hybrid format. This comprehensive book encompasses the proceedings of the conference, featuring 14 full papers that were meticulously reviewed and chosen from a pool of 70 submissions. The papers were organized into topical sections, covering various aspects of big data analytics, including:

Big Data Analytics: This section encompassed papers that explored innovative techniques and methodologies for analyzing large and complex datasets, such as data mining, machine learning, and artificial intelligence.

Networking: The papers in this section focused on developing and improving network technologies and algorithms for handling big data, such as distributed computing, cloud computing, and network optimization.

Social Media: This section explored the analysis of social media data to understand user behavior, social networks, and social trends, using techniques such as natural language processing, sentiment analysis, and network analysis.

Search: The papers in this section addressed the challenges and opportunities of search engine optimization, web crawling, and information retrieval in the context of big data.

Information Extraction: This section explored techniques for extracting relevant information from unstructured and semi-structured data sources, such as text, images, and videos, using methods such as text mining, machine learning, and natural language processing.

Image Processing and Analysis: The papers in this section focused on developing and applying image processing and analysis techniques for various applications, such as medical imaging, surveillance, and remote sensing.

Spatial Data Analysis: This section explored the analysis of spatial data, including geographic information systems, geospatial analysis, and spatial statistics, to address real-world problems such as urban planning, environmental monitoring, and transportation.

Text Data Analysis: The papers in this section addressed the analysis of textual data, including social media posts, news articles, and scientific papers, using techniques such as text mining, sentiment analysis, and topic modeling.

Mobile and Graph Data Analysis: This section explored the analysis of mobile and graph data, including data from mobile devices, social networks, and other graph-structured data sources, using techniques such as data mining, machine learning, and graph theory.

Machine Learning: The papers in this section addressed the development and application of machine learning algorithms for various tasks, such as classification, regression, and prediction, in the context of big data.

Healthcare: The papers in this section explored the use of big data analytics in healthcare, including disease diagnosis, patient monitoring, and drug discovery.

The 10th International Conference on Big Data Analytics, BDA 2022, brought together experts and researchers from around the world to discuss the latest advancements and challenges in big data analytics. The conference provided a platform for exchanging ideas, sharing research findings, and fostering collaborations in this rapidly evolving field.

The selection process for the papers included in this volume was rigorous, with each submission being evaluated based on its originality, significance, and relevance to the conference theme. The conference committee comprised prominent researchers and practitioners in the field of big data analytics, ensuring that the most cutting-edge and impactful research was included in the proceedings.

The 14 full papers included in this volume represent a diverse range of research areas and methodologies, showcasing the latest developments in big data analytics. The papers cover topics such as big data infrastructure, data visualization, data quality assessment, data privacy and security, and machine learning for healthcare.

The conference proceedings also included keynote speeches, panel discussions, and workshops, which provided opportunities for participants to engage with experts in the field and learn about the latest trends and applications in big data analytics.

In conclusion, the 10th International Conference on Big Data Analytics, BDA 2022, was a successful event that brought together researchers, practitioners, and industry professionals from around the world to explore the latest developments and applications in big data analytics. The conference proceedings in this book provide a valuable resource for anyone interested in this field, offering insights into the latest techniques, methodologies, and applications in big data analytics.

The 10th International Conference on Big Data Analytics, BDA 2022, was held in Aizu, Japan, in December 2022, in a hybrid format. This comprehensive book encompasses the proceedings of the conference, featuring 14 full papers that were meticulously reviewed and chosen from a pool of 70 submissions. The papers were organized into topical sections, covering various aspects of big data analytics, including:

Big Data Analytics: This section encompassed papers that explored innovative techniques and methodologies for analyzing large and complex datasets, such as data mining, machine learning, and artificial intelligence.

Networking: The papers in this section focused on developing and improving network technologies and algorithms for handling big data, such as distributed computing, cloud computing, and network optimization.

Social Media: This section explored the analysis of social media data to understand user behavior, social networks, and social trends, using techniques such as natural language processing, sentiment analysis, and network analysis.

Search: The papers in this section addressed the challenges and opportunities of search engine optimization, web crawling, and information retrieval in the context of big data.

Information Extraction: This section explored techniques for extracting relevant information from unstructured and semi-structured data sources, such as text, images, and videos, using methods such as text mining, machine learning, and natural language processing.

Image Processing and Analysis: The papers in this section focused on developing and applying image processing and analysis techniques for various applications, such as medical imaging, surveillance, and remote sensing.

Spatial Data Analysis: This section explored the analysis of spatial data, including geographic information systems, geospatial analysis, and spatial statistics, to address real-world problems such as urban planning, environmental monitoring, and transportation.

Text Data Analysis: The papers in this section addressed the analysis of textual data, including social media posts, news articles, and scientific papers, using techniques such as text mining, sentiment analysis, and topic modeling.

Mobile and Graph Data Analysis: This section explored the analysis of mobile and graph data, including data from mobile devices, social networks, and other graph-structured data sources, using techniques such as data mining, machine learning, and graph theory.

Machine Learning: The papers in this section addressed the development and application of machine learning algorithms for various tasks, such as classification, regression, and prediction, in the context of big data.

Healthcare: The papers in this section explored the use of big data analytics in healthcare, including disease diagnosis, patient monitoring, and drug discovery.

The 10th International Conference on Big Data Analytics, BDA 2022, brought together experts and researchers from around the world to discuss the latest advancements and challenges in big data analytics. The conference provided a platform for exchanging ideas, sharing research findings, and fostering collaborations in this rapidly evolving field.

The selection process for the papers included in this volume was rigorous, with each submission being evaluated based on its originality, significance, and relevance to the conference theme. The conference committee comprised prominent researchers and practitioners in the field of big data analytics, ensuring that the most cutting-edge and impactful research was included in the proceedings.

The 14 full papers included in this volume represent a diverse range of research areas and methodologies, showcasing the latest developments in big data analytics. The papers cover topics such as big data infrastructure, data visualization, data quality assessment, data privacy and security, and machine learning for healthcare.

The conference proceedings also included keynote speeches, panel discussions, and workshops, which provided opportunities for participants to engage with experts in the field and learn about the latest trends and applications in big data analytics.

In conclusion, the 10th International Conference on Big Data Analytics, BDA 2022, was a successful event that brought together researchers, practitioners, and industry professionals from around the world to explore the latest developments and applications in big data analytics. The conference proceedings in this book provide a valuable resource for anyone interested in this field, offering insights into the latest techniques, methodologies, and applications in big data analytics.

The 10th International Conference on Big Data Analytics, BDA 2022, was held in Aizu, Japan, in December 2022, in a hybrid format. This comprehensive book encompasses the proceedings of the conference, featuring 14 full papers that were meticulously reviewed and chosen from a pool of 70 submissions. The papers were organized into topical sections, covering various aspects of big data analytics, including:

Big Data Analytics: This section encompassed papers that explored innovative techniques and methodologies for analyzing large and complex datasets, such as data mining, machine learning, and artificial intelligence.

Networking: The papers in this section focused on developing and improving network technologies and algorithms for handling big data, such as distributed computing, cloud computing, and network optimization.

Social Media: This section explored the analysis of social media data to understand user behavior, social networks, and social trends, using techniques such as natural language processing, sentiment analysis, and network analysis.

Search: The papers in this section addressed the challenges and opportunities of search engine optimization, web crawling, and information retrieval in the context of big data.

Information Extraction: This section explored techniques for extracting relevant information from unstructured and semi-structured data sources, such as text, images, and videos, using methods such as text mining, machine learning, and natural language processing.

Image Processing and Analysis: The papers in this section focused on developing and applying image processing and analysis techniques for various applications, such as medical imaging, surveillance, and remote sensing.

Spatial Data Analysis: This section explored the analysis of spatial data, including geographic information systems, geospatial analysis, and spatial statistics, to address real-world problems such as urban planning, environmental monitoring, and transportation.

Text Data Analysis: The papers in this section addressed the analysis of textual data, including social media posts, news articles, and scientific papers, using techniques such as text mining, sentiment analysis, and topic modeling.

Mobile and Graph Data Analysis: This section explored the analysis of mobile and graph data, including data from mobile devices, social networks, and other graph-structured data sources, using techniques such as data mining, machine learning, and graph theory.

Machine Learning: The papers in this section addressed the development and application of machine learning algorithms for various tasks, such as classification, regression, and prediction, in the context of big data.

Healthcare: The papers in this section explored the use of big data analytics in healthcare, including disease diagnosis, patient monitoring, and drug discovery.

The 10th International Conference on Big Data Analytics, BDA 2022, brought together experts and researchers from around the world to discuss the latest advancements and challenges in big data analytics. The conference provided a platform for exchanging ideas, sharing research findings, and fostering collaborations in this rapidly evolving field.

The selection process for the papers included in this volume was rigorous, with each submission being evaluated based on its originality, significance, and relevance to the conference theme. The conference committee comprised prominent researchers and practitioners in the field of big data analytics, ensuring that the most cutting-edge and impactful research was included in the proceedings.

The 14 full papers included in this volume represent a diverse range of research areas and methodologies, showcasing the latest developments in big data analytics. The papers cover topics such as big data infrastructure, data visualization, data quality assessment, data privacy and security, and machine learning for healthcare.

The conference proceedings also included keynote speeches, panel discussions, and workshops, which provided opportunities for participants to engage with experts in the field and learn about the latest trends and applications in big data analytics.

In conclusion, the 10th International Conference on Big Data Analytics, BDA 2022, was a successful event that brought together researchers, practitioners, and industry professionals from around the world to explore the latest developments and applications in big data analytics. The conference proceedings in this book provide a valuable resource for anyone interested in this field, offering insights into the latest techniques, methodologies, and applications in big data analytics.

Weight: 403g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031283499
Edition number: 1st ed. 2023