9783031333736-303133373X-Advances in Knowledge Discovery and Data Mining: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May ... I (Lecture Notes in Computer Science, 13935)

Advances in Knowledge Discovery and Data Mining: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May ... I (Lecture Notes in Computer Science, 13935)

ISBN-13: 9783031333736
ISBN-10: 303133373X
Edition: 1st ed. 2023
Author: Tsuyoshi Ide, Hisashi Kashima, Wen-Chih Peng
Publication date: 2023
Publisher: Springer
Format: Paperback 576 pages
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Book details

ISBN-13: 9783031333736
ISBN-10: 303133373X
Edition: 1st ed. 2023
Author: Tsuyoshi Ide, Hisashi Kashima, Wen-Chih Peng
Publication date: 2023
Publisher: Springer
Format: Paperback 576 pages

Summary

Advances in Knowledge Discovery and Data Mining: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May ... I (Lecture Notes in Computer Science, 13935) (ISBN-13: 9783031333736 and ISBN-10: 303133373X), written by authors Tsuyoshi Ide, Hisashi Kashima, Wen-Chih Peng, was published by Springer in 2023. With an overall rating of 4.5 stars, it's a notable title among other books. You can easily purchase or rent Advances in Knowledge Discovery and Data Mining: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May ... I (Lecture Notes in Computer Science, 13935) (Paperback) from BooksRun, along with many other new and used books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.49.

Description

The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25-28, 2023.
The 143 papers presented in these proceedings were carefully reviewed and selected from 813 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.

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