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Advances in IoT and Security with Computational Intelligence: Proceedings of ICAISA 2023, Volume 1 (Lecture Notes in Networks and Systems #755)
by Anurag Mishra Deepak Gupta Girija ChettyThe book is a collection of peer-reviewed best-selected research papers presented at the International Conference on Advances in IoT and Security with AI (ICAISA 2023), organized by Deen Dayal Upadhyaya College, University of Delhi, New Delhi, India, in collaboration with University of Canberra, Canberra, Australia, and NIT, Arunachal Pradesh, Itanagar, AP, India, during March 24–25, 2023. The book includes various applications and technologies in this specialized sector of Industry 4.0. The book is divided into two volumes. It focuses on recent advances in Internet of Things and security with its applications using artificial intelligence.
Advances in IoT and Security with Computational Intelligence: Proceedings of ICAISA 2023, Volume 2 (Lecture Notes in Networks and Systems #756)
by Anurag Mishra Deepak Gupta Girija ChettyThe book is a collection of peer-reviewed best-selected research papers presented at the International Conference on Advances in IoT and Security with AI (ICAISA 2023), organized by Deen Dayal Upadhyaya College, University of Delhi, New Delhi, India, in collaboration with University of Canberra, Canberra, Australia, and NIT, Arunachal Pradesh, Itanagar, AP, India, during March 24–25, 2023. The book includes various applications and technologies in this specialized sector of Industry 4.0. The book is divided into two volumes. It focuses on recent advances in Internet of Things and security with its applications using artificial intelligence.
Advances in K-means Clustering: A Data Mining Thinking (Springer Theses)
by Junjie WuNearly everyone knows K-means algorithm in the fields of data mining and business intelligence. But the ever-emerging data with extremely complicated characteristics bring new challenges to this "old" algorithm. This book addresses these challenges and makes novel contributions in establishing theoretical frameworks for K-means distances and K-means based consensus clustering, identifying the "dangerous" uniform effect and zero-value dilemma of K-means, adapting right measures for cluster validity, and integrating K-means with SVMs for rare class analysis. This book not only enriches the clustering and optimization theories, but also provides good guidance for the practical use of K-means, especially for important tasks such as network intrusion detection and credit fraud prediction. The thesis on which this book is based has won the "2010 National Excellent Doctoral Dissertation Award", the highest honor for not more than 100 PhD theses per year in China.
Advances in Knowledge Discovery and Data Mining: 20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part I (Lecture Notes in Computer Science #9651)
by James Bailey Ruili Wang Latifur Khan Takashi Washio Gill Dobbie Joshua Zhexue HuangThis two-volume set, LNAI 9651 and 9652, constitutes thethoroughly refereed proceedings of the 20th Pacific-Asia Conference on Advancesin Knowledge Discovery and Data Mining, PAKDD 2016, held in Auckland, NewZealand, in April 2016. The 91 full papers were carefully reviewed andselected from 307 submissions. They are organized in topical sections named:classification; machine learning; applications; novel methods and algorithms;opinion mining and sentiment analysis; clustering; feature extraction andpattern mining; graph and network data; spatiotemporal and image data; anomalydetection and clustering; novel models and algorithms; and text mining andrecommender systems.
Advances in Knowledge Discovery and Data Mining: 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part I (Lecture Notes in Computer Science #10234)
by Jinho Kim, Kyuseok Shim, Longbing Cao, Jae-Gil Lee, Xuemin Lin and Yang-Sae MoonThis two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.
Advances in Knowledge Discovery and Data Mining: 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part II (Lecture Notes in Computer Science #10235)
by Jinho Kim, Kyuseok Shim, Longbing Cao, Jae-Gil Lee, Xuemin Lin and Yang-Sae MoonThis two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.
Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part I (Lecture Notes in Computer Science #10937)
by Geoffrey I. Webb Vincent S. Tseng Dinh Phung Bao Ho Mohadeseh Ganji Lida RashidiThis three-volume set, LNAI 10937, 10938, and 10939, constitutes the thoroughly refereed proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018. The 164 full papers were carefully reviewed and selected from 592 submissions. The volumes present papers focusing on 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.
Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part II (Lecture Notes in Computer Science #10938)
by Geoffrey I. Webb Vincent S. Tseng Dinh Phung Bao Ho Mohadeseh Ganji Lida RashidiThis three-volume set, LNAI 10937, 10938, and 10939, constitutes the thoroughly refereed proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018. The 164 full papers were carefully reviewed and selected from 592 submissions. The volumes present papers focusing on 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.
Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part III (Lecture Notes in Computer Science #10939)
by Geoffrey I. Webb Vincent S. Tseng Dinh Phung Bao Ho Mohadeseh Ganji Lida RashidiThis three-volume set, LNAI 10937, 10938, and 10939, constitutes the thoroughly refereed proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018. The 164 full papers were carefully reviewed and selected from 592 submissions. The volumes present papers focusing on 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.
Advances in Knowledge Discovery and Data Mining: 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings, Part I (Lecture Notes in Computer Science #11439)
by Zhi-Hua Zhou Zhiguo Gong Min-Ling Zhang Qiang Yang Sheng-Jun HuangThe three-volume set LNAI 11439, 11440, and 11441 constitutes the thoroughly refereed proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019. The 137 full papers presented were carefully reviewed and selected from 542 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: classification and supervised learning; text and opinion mining; spatio-temporal and stream data mining; factor and tensor analysis; healthcare, bioinformatics and related topics; clustering and anomaly detection; deep learning models and applications; sequential pattern mining; weakly supervised learning; recommender system; social network and graph mining; data pre-processing and feature selection; representation learning and embedding; mining unstructured and semi-structured data; behavioral data mining; visual data mining; and knowledge graph and interpretable data mining.
Advances in Knowledge Discovery and Data Mining: 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings, Part II (Lecture Notes in Computer Science #11440)
by Zhi-Hua Zhou Zhiguo Gong Min-Ling Zhang Qiang Yang Sheng-Jun HuangThe three-volume set LNAI 11439, 11440, and 11441 constitutes the thoroughly refereed proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019. The 137 full papers presented were carefully reviewed and selected from 542 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: classification and supervised learning; text and opinion mining; spatio-temporal and stream data mining; factor and tensor analysis; healthcare, bioinformatics and related topics; clustering and anomaly detection; deep learning models and applications; sequential pattern mining; weakly supervised learning; recommender system; social network and graph mining; data pre-processing and featureselection; representation learning and embedding; mining unstructured and semi-structured data; behavioral data mining; visual data mining; and knowledge graph and interpretable data mining.
Advances in Knowledge Discovery and Data Mining: 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings, Part III (Lecture Notes in Computer Science #11441)
by Zhi-Hua Zhou Zhiguo Gong Min-Ling Zhang Qiang Yang Sheng-Jun HuangThe three-volume set LNAI 11439, 11440, and 11441 constitutes the thoroughly refereed proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019. The 137 full papers presented were carefully reviewed and selected from 542 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: classification and supervised learning; text and opinion mining; spatio-temporal and stream data mining; factor and tensor analysis; healthcare, bioinformatics and related topics; clustering and anomaly detection; deep learning models and applications; sequential pattern mining; weakly supervised learning; recommender system; social network and graph mining; data pre-processing and featureselection; representation learning and embedding; mining unstructured and semi-structured data; behavioral data mining; visual data mining; and knowledge graph and interpretable data mining.
Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part I (Lecture Notes in Computer Science #12084)
by Ee-Peng Lim Raymond Chi-Wing Wong See-Kiong Ng Hady W. Lauw Alexandros Ntoulas Sinno Jialin PanThe 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: 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part II (Lecture Notes in Computer Science #12085)
by Ee-Peng Lim Raymond Chi-Wing Wong See-Kiong Ng Hady W. Lauw Alexandros Ntoulas Sinno Jialin PanThe 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.
Advances in Knowledge Discovery and Data Mining: 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part I (Lecture Notes in Computer Science #12712)
by Hong Cheng Jaideep Srivastava P. Krishna Reddy Tanmoy Chakraborty Naren Ramakrishnan Kamal Karlapalem R. K. AgrawalThe 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: 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part II (Lecture Notes in Computer Science #12713)
by Hong Cheng Jaideep Srivastava P. Krishna Reddy Tanmoy Chakraborty Naren Ramakrishnan Kamal Karlapalem R. K. AgrawalThe 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: 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part III (Lecture Notes in Computer Science #12714)
by Hong Cheng Jaideep Srivastava P. Krishna Reddy Tanmoy Chakraborty Naren Ramakrishnan Kamal Karlapalem R. K. AgrawalThe 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: 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16–19, 2022, Proceedings, Part I (Lecture Notes in Computer Science #13280)
by Yu Zheng Yang Yu Tianrui Li João Gama Enhong Chen Fei TengThe 3-volume set LNAI 13280, LNAI 13281 and LNAI 13282 constitutes the proceedings of the 26th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2022, which was held during May 2022 in Chengdu, China. The 121 papers included in the proceedings were carefully reviewed and selected from a total of 558 submissions. They were organized in topical sections as follows: Part I: Data Science and Big Data Technologies, Part II: Foundations; and Part III: Applications.
Advances in Knowledge Discovery and Data Mining: 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16–19, 2022, Proceedings, Part II (Lecture Notes in Computer Science #13281)
by Yu Zheng Yang Yu Tianrui Li João Gama Enhong Chen Fei TengThe 3-volume set LNAI 13280, LNAI 13281 and LNAI 13282 constitutes the proceedings of the 26th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2022, which was held during May 2022 in Chengdu, China. The 121 papers included in the proceedings were carefully reviewed and selected from a total of 558 submissions. They were organized in topical sections as follows: Part I: Data Science and Big Data Technologies, Part II: Foundations; and Part III: Applications.
Advances in Knowledge Discovery and Data Mining: 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16–19, 2022, Proceedings, Part III (Lecture Notes in Computer Science #13282)
by Yu Zheng Yang Yu Tianrui Li João Gama Enhong Chen Fei TengThe 3-volume set LNAI 13280, LNAI 13281 and LNAI 13282 constitutes the proceedings of the 26th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2022, which was held during May 2022 in Chengdu, China. The 121 papers included in the proceedings were carefully reviewed and selected from a total of 558 submissions. They were organized in topical sections as follows: Part I: Data Science and Big Data Technologies, Part II: Foundations; and Part III: Applications.
Advances in Knowledge Discovery and Data Mining: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part I (Lecture Notes in Computer Science #13935)
by Wen-Chih Peng Hisashi Kashima Tsuyoshi IdeThe 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: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part II (Lecture Notes in Computer Science #13936)
by Wen-Chih Peng Hisashi Kashima Tsuyoshi IdeThe 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: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part III (Lecture Notes in Computer Science #13937)
by Wen-Chih Peng Hisashi Kashima Tsuyoshi IdeThe 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: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part IV (Lecture Notes in Computer Science #13938)
by Wen-Chih Peng Hisashi Kashima Tsuyoshi IdeThe 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: 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part I (Lecture Notes in Computer Science #14645)
by Vincent S. Tseng Jerry Chun-Wei Lin Xing Xie Jian Pei De-Nian Yang Jen-Wei HuangThe 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7–10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 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.