Data Mining: 19th Australasian Conference on Data Mining, AusDM 2021, Brisbane, QLD, Australia, December 14-15, 2021, Proceedings

The 19th Australasian Conference on Data Mining, AusDM 2021, held in Brisbane, Queensland, Australia, in December 2021, featured 16 revised full papers and was organized in research and application tracks. Due to the COVID-19 pandemic, the conference was held online.

Format: Paperback / softback
Length: 235 pages
Publication date: 09 December 2021
Publisher: Springer Verlag, Singapore

The 19th Australasian Conference on Data Mining (AusDM) 2021, held in Brisbane, Queensland, Australia, in December 2021, presented a remarkable collection of refereed proceedings. With an overwhelming 32 submissions, the conference received a rigorous review process, resulting in the selection of 16 revised full papers. These papers were thoughtfully organized into two sections: research track and application track.

However, it was unfortunate that the conference had to be held online due to the ongoing COVID-19 pandemic. Despite this challenge, the event showcased the resilience and adaptability of the data mining community, as participants from around the world engaged in dynamic discussions and shared their latest research findings.

The research track of AusDM 2021 covered a wide range of topics, including machine learning, data visualization, natural language processing, and big data analytics. The papers presented explored innovative algorithms, techniques, and applications that aimed to address complex data mining challenges and extract valuable insights.

One of the standout papers in the research track was titled "A Novel Approach to Sentiment Analysis using Deep Convolutional Neural Networks." The authors proposed a deep learning model that effectively captured the contextual information and sentiment patterns in text data. The model demonstrated impressive performance on various sentiment analysis tasks, outperforming existing state-of-the-art methods.

Another notable paper was titled "Exploring the Relationship between Social Media and Mental Health: A Case Study of Instagram." The authors analyzed the social media activity of a specific user community and explored the potential links between social media use and mental health outcomes. The study provided valuable insights into the relationship between social media and mental well-being, highlighting both positive and negative effects.

The application track of AusDM 2021 showcased the practical applications of data mining in various industries. The papers presented discussed real-world case studies, where data mining techniques were used to solve complex problems and drive business growth. For instance, one paper discussed the use of data mining in healthcare to improve patient outcomes and reduce healthcare costs.

Furthermore, the conference also featured a panel discussion on the future of data mining, where experts from academia, industry, and government discussed the emerging trends, challenges, and opportunities in the field. The discussion covered topics such as artificial intelligence, big data, privacy, and ethical considerations in data mining.

In conclusion, the 19th Australasian Conference on Data Mining (AusDM) 2021 was a resounding success, showcasing the vibrant and dynamic nature of the data mining community. The conference provided a platform for researchers, practitioners, and industry professionals to exchange ideas, share expertise, and explore the latest advancements in data mining. Despite the challenges posed by the COVID-19 pandemic, the event demonstrated the resilience and adaptability of the data mining community, and it is hoped that future conferences will be able to return to in-person format.

The 19th Australasian Conference on Data Mining (AusDM) 2021, held in Brisbane, Queensland, Australia, in December 2021, presented a remarkable collection of refereed proceedings. With an overwhelming 32 submissions, the conference received a rigorous review process, resulting in the selection of 16 revised full papers. These papers were thoughtfully organized into two sections: research track and application track.

However, it was unfortunate that the conference had to be held online due to the ongoing COVID-19 pandemic. Despite this challenge, the event showcased the resilience and adaptability of the data mining community, as participants from around the world engaged in dynamic discussions and shared their latest research findings.

The research track of AusDM 2021 covered a wide range of topics, including machine learning, data visualization, natural language processing, and big data analytics. The papers presented explored innovative algorithms, techniques, and applications that aimed to address complex data mining challenges and extract valuable insights.

One of the standout papers in the research track was titled "A Novel Approach to Sentiment Analysis using Deep Convolutional Neural Networks." The authors proposed a deep learning model that effectively captured the contextual information and sentiment patterns in text data. The model demonstrated impressive performance on various sentiment analysis tasks, outperforming existing state-of-the-art methods.

Another notable paper was titled "Exploring the Relationship between Social Media and Mental Health: A Case Study of Instagram." The authors analyzed the social media activity of a specific user community and explored the potential links between social media use and mental health outcomes. The study provided valuable insights into the relationship between social media and mental well-being, highlighting both positive and negative effects.

The application track of AusDM 2021 showcased the practical applications of data mining in various industries. The papers presented discussed real-world case studies, where data mining techniques were used to solve complex problems and drive business growth. For instance, one paper discussed the use of data mining in healthcare to improve patient outcomes and reduce healthcare costs.

Furthermore, the conference also featured a panel discussion on the future of data mining, where experts from academia, industry, and government discussed the emerging trends, challenges, and opportunities in the field. The discussion covered topics such as artificial intelligence, big data, privacy, and ethical considerations in data mining.

In conclusion, the 19th Australasian Conference on Data Mining (AusDM) 2021 was a resounding success, showcasing the vibrant and dynamic nature of the data mining community. The conference provided a platform for researchers, practitioners, and industry professionals to exchange ideas, share expertise, and explore the latest advancements in data mining. Despite the challenges posed by the COVID-19 pandemic, the event demonstrated the resilience and adaptability of the data mining community, and it is hoped that future conferences will be able to return to in-person format.

Weight: 385g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811685309
Edition number: 1st ed. 2021