Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia Conference, Pakdd 2020, Singapore, May 11-14, 2020, Proceedings, Part II
暫譯: 知識發現與數據挖掘的進展:第24屆亞太會議,Pakdd 2020,新加坡,2020年5月11-14日,會議論文集,第二部分
Lauw, Hady W., Wong, Raymond Chi, Ntoulas, Alexandros
- 出版商: Springer
- 出版日期: 2020-05-09
- 售價: $4,560
- 貴賓價: 9.5 折 $4,332
- 語言: 英文
- 頁數: 924
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3030474356
- ISBN-13: 9783030474355
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相關分類:
Data-mining
海外代購書籍(需單獨結帳)
商品描述
The two-volume set LNAI 12084 and 12085 constitutes the thoroughly refereed proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, held in Singapore, in May 2020.
The 135 full papers presented were carefully reviewed and selected from 628 submissions. The papers present 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, visualization, decision-making systems, and the emerging applications. They are organized in the following topical sections: recommender systems; classification; clustering; mining social networks; representation learning and embedding; mining behavioral data; deep learning; feature extraction and selection; human, domain, organizational and social factors in data mining; mining sequential data; mining imbalanced data; association; privacy and security; supervised learning; novel algorithms; mining multi-media/multi-dimensional data; application; mining graph and network data; anomaly detection and analytics; mining spatial, temporal, unstructured and semi-structured data; sentiment analysis; statistical/graphical model; multi-source/distributed/parallel/cloud computing.
商品描述(中文翻譯)
這兩卷的 LNAI 12084 和 12085 是第 24 屆亞太知識發現與數據挖掘會議(PAKDD 2020)經過徹底審稿的會議論文集,該會議於 2020 年 5 月在新加坡舉行。
所呈現的 135 篇完整論文是從 628 篇投稿中仔細審核和選出的。這些論文展示了來自所有 KDD 相關領域的新想法、原創研究成果和實際開發經驗,包括數據挖掘、數據倉儲、機器學習、人工智慧、數據庫、統計學、知識工程、可視化、決策系統以及新興應用。論文被組織在以下主題部分:推薦系統;分類;聚類;社交網絡挖掘;表示學習與嵌入;行為數據挖掘;深度學習;特徵提取與選擇;數據挖掘中的人、領域、組織和社會因素;序列數據挖掘;不平衡數據挖掘;關聯;隱私與安全;監督學習;新穎算法;多媒體/多維數據挖掘;應用;圖形和網絡數據挖掘;異常檢測與分析;空間、時間、非結構化和半結構化數據挖掘;情感分析;統計/圖形模型;多源/分佈式/並行/雲計算。