Advances in Knowledge Discovery and Data Mining

This collection features the proceedings from the 20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, showcasing significant research in the field.

This two-volume set, LNAI 9651 and 9652, presents the thoroughly refereed proceedings of the 20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2016, which took place in Auckland, New Zealand, in April 2016. It showcases a collection of 91 full papers that were meticulously reviewed and selected from a total of 307 submissions, ensuring that only the most impactful research is included.

The content is organized into various topical sections, covering critical areas such as classification, machine learning, and novel methods and algorithms. Each section highlights the latest advancements and applications in the field, providing valuable insights into opinion mining, sentiment analysis, and clustering techniques. The diverse range of topics reflects the current trends and challenges in knowledge discovery and data mining.

In Advances in Knowledge Discovery and Data Mining, readers will find discussions on feature extraction, pattern mining, and various data types, including spatiotemporal and image data. The proceedings also address anomaly detection and clustering, along with innovative models and algorithms. This comprehensive collection serves as an essential resource for researchers and practitioners who are looking to stay updated on the evolving landscape of data mining and knowledge discovery.