Advances In Knowledge Discovery And Data Mining Part I
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Advances In Knowledge Discovery And Data Mining Part I
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Author : Pang-Ning Tan
language : en
Publisher: Springer
Release Date : 2012-05-10
Advances In Knowledge Discovery And Data Mining Part I written by Pang-Ning Tan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-10 with Computers categories.
The two-volume set LNAI 7301 and 7302 constitutes the refereed proceedings of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2012, held in Kuala Lumpur, Malaysia, in May 2012. The total of 20 revised full papers and 66 revised short papers were carefully reviewed and selected from 241 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas. The papers are organized in topical sections on supervised learning: active, ensemble, rare-class and online; unsupervised learning: clustering, probabilistic modeling in the first volume and on pattern mining: networks, graphs, time-series and outlier detection, and data manipulation: pre-processing and dimension reduction in the second volume.
Advances In Knowledge Discovery And Data Mining
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Author : Hady W. Lauw
language : en
Publisher: Springer Nature
Release Date : 2020-05-08
Advances In Knowledge Discovery And Data Mining written by Hady W. Lauw and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-08 with Computers categories.
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, which was due to be held in Singapore, in May 2020. The conference was held virtually due to the COVID-19 pandemic. 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.
Advances In Knowledge Discovery And Data Mining Part I
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Author : Mohammed J. Zaki
language : en
Publisher: Springer Science & Business Media
Release Date : 2010
Advances In Knowledge Discovery And Data Mining Part I written by Mohammed J. Zaki and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Artificial intelligence categories.
Advances In Knowledge Discovery And Data Mining
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Author : Kamal Karlapalem
language : en
Publisher: Springer Nature
Release Date : 2021-05-07
Advances In Knowledge Discovery And Data Mining written by Kamal Karlapalem and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-07 with Computers categories.
The 3-volume set LNAI 12712-12714 constitutes the proceedings of the 25th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2021, which was held during May 11-14, 2021. The 157 papers included in the proceedings were carefully reviewed and selected from a total of 628 submissions. They were organized in topical sections as follows: Part I: Applications of knowledge discovery and data mining of specialized data; Part II: Classical data mining; data mining theory and principles; recommender systems; and text analytics; Part III: Representation learning and embedding, and learning from data.
Advances In Knowledge Discovery And Data Mining
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Author : Kamal Karlapalem
language : en
Publisher: Springer Nature
Release Date : 2021-05-07
Advances In Knowledge Discovery And Data Mining written by Kamal Karlapalem and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-07 with Computers categories.
The 3-volume set LNAI 12712-12714 constitutes the proceedings of the 25th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2021, which was held during May 11-14, 2021. The 157 papers included in the proceedings were carefully reviewed and selected from a total of 628 submissions. They were organized in topical sections as follows: Part I: Applications of knowledge discovery and data mining of specialized data; Part II: Classical data mining; data mining theory and principles; recommender systems; and text analytics; Part III: Representation learning and embedding, and learning from data.
Advances In Knowledge Discovery And Data Mining
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Author : Hady W. Lauw
language : en
Publisher: Springer Nature
Release Date : 2020-05-08
Advances In Knowledge Discovery And Data Mining written by Hady W. Lauw and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-08 with Computers categories.
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, which was due to be held in Singapore, in May 2020. The conference was held virtually due to the COVID-19 pandemic. 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.
Advances In Knowledge Discovery And Data Mining
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Author : Vincent S. Tseng
language : en
Publisher: Springer
Release Date : 2014-05-08
Advances In Knowledge Discovery And Data Mining written by Vincent S. Tseng and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-08 with Computers categories.
The two-volume set LNAI 8443 + LNAI 8444 constitutes the refereed proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014, held in Tainan, Taiwan, in May 2014. The 40 full papers and the 60 short papers presented within these proceedings were carefully reviewed and selected from 371 submissions. They cover the general fields of pattern mining; social network and social media; classification; graph and network mining; applications; privacy preserving; recommendation; feature selection and reduction; machine learning; temporal and spatial data; novel algorithms; clustering; biomedical data mining; stream mining; outlier and anomaly detection; multi-sources mining; and unstructured data and text mining.
Advances In Knowledge Discovery And Management
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Author : Fabrice Guillet
language : en
Publisher: Springer
Release Date : 2010-09-07
Advances In Knowledge Discovery And Management written by Fabrice Guillet and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-07 with Computers categories.
During the last decade, the French-speaking scientific community developed a very strong research activity in the field of Knowledge Discovery and Management (KDM or EGC for “Extraction et Gestion des Connaissances” in French), which is concerned with, among others, Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and SemanticWeb. The recent and novel research contributions collected in this book are extended and reworked versions of a selection of the best papers that were originally presented in French at the EGC 2009 Conference held in Strasbourg, France on January 2009. The volume is organized in four parts. Part I includes five papers concerned by various aspects of supervised learning or information retrieval. Part II presents five papers concerned with unsupervised learning issues. Part III includes two papers on data streaming and two on security while in Part IV the last four papers are concerned with ontologies and semantic.
Advances In Knowledge Discovery And Data Mining
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Author : Hisashi Kashima
language : en
Publisher: Springer Nature
Release Date : 2023-05-26
Advances In Knowledge Discovery And Data Mining written by Hisashi Kashima and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-26 with Computers categories.
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.
Advances In Knowledge Discovery And Data Mining
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Author : Xintao Wu
language : en
Publisher: Springer Nature
Release Date : 2025-07-19
Advances In Knowledge Discovery And Data Mining written by Xintao Wu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-19 with Computers categories.
The five-volume set, LNAI 158710 - 15874 constitutes the proceedings of the 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025, held in Sydney, New South Wales, Australia, during June 10–13, 2025. The conference received a total of 557 submissions to the main track, 35 submissions to the survey track and 104 submittion to the special track on LLMs. Of these, 134 papers have been accepted for the main track, 10 for the survey track and 24 for the LLM track. 68 papers have been transferred to the4 DSFA special session. The papers have been organized in topical sections as follows: Part I: Anomaly Detection; Business Data Analysis; Clustering; Continual Learning; Contrastive Learning; Data Processing for Learning; Part II: Fairness and Interpretability; Federated Learning; Graph Mining and GNN; Learning on Scientific Data; Part III: Machine Learning; Multi-modality; OOD and Optimization; Recommender Systems; Representation Learning and Generative AI; Part IV: Security and Privacy; Temporal Learning; Survey; Part V: LLM Fine-tuning and Prompt Engineering; Fairness and Interpretability of LLMs; LLM Application; OOD and Optimization of LLMs.