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Instance Selection and Construction for Data Mining
The ability to analyze and understand massive data sets lags far behind the ability to gather and store the data. To meet this challenge, knowledge discovery and data mining (KDD) is growing rapidly as an emerging field. However, no matter how powerful computers are now or will be in the future, KDD researchers and practitioners must consider how to manage ever-growing data which is, ironically, due to the extensive use of computers and ease of data collection with computers. Many different approaches have been used to address the data explosion issue, such as algorithm scale-up and data reduction. Instance, example, or tuple selection pertains to methods or algorithms that select or search ...
AI 2006: Advances in Artificial Intelligence
This book constitutes the refereed proceedings of the 19th Australian Joint Conference on Artificial Intelligence, AI 2006, held in Hobart, Australia, December 2006. Coverage includes foundations and knowledge based system, machine learning, connectionist AI, data mining, intelligent agents, cognition and user interface, vision and image processing, natural language processing and Web intelligence, neural networks, robotics, and AI applications.
Knowledge Engineering and Management
"Knowledge Engineering and Management" presents selected papers from the 2013 International Conference on Intelligent Systems and Knowledge Engineering (ISKE2013). The aim of this conference is to bring together experts from different expertise areas to discuss the state-of-the-art in Intelligent Systems and Knowledge Engineering, and to present new research results and perspectives on future development. The topics in this volume include, but not limited to: Knowledge Representation and Modeling, Knowledge Maintenance, Knowledge Elicitation, Knowledge-Based Systems (KBS), Content Management and Knowledge Management Systems, Ontology Engineering, Data Mining and Knowledge Discovery, Knowledge Acquisition, etc. The proceedings are benefit for both researchers and practitioners who want to utilize knowledge engineering methods in their specific research fields. Dr. Zhenkun Wen is a Professor at the College of Computer and Software Engineering, Shenzhen University, China. Dr. Tianrui Li is a Professor at the School of Information Science and Technology, Southwest Jiaotong University, Xi’an, China.
Advances in Artificial Intelligence
AI 2001 is the 14th in the series of Arti cial Intelligence conferences sponsored by the Canadian Society for Computational Studies of Intelligence/Soci et e - nadienne pour l’ etude de l’intelligence par ordinateur. As was the case last year too, the conference is being held in conjunction with the annual conferences of two other Canadian societies, Graphics Interface (GI 2001) and Vision Int- face (VI 2001). We believe that the overall experience will be enriched by this conjunction of conferences. This year is the \silver anniversary" of the conference: the rst Canadian AI conference was held in 1976 at UBC. During its lifetime, it has attracted Canadian and international papers of high quality from a variety of AI research areas. All papers submitted to the conference received at least three indep- dent reviews. Approximately one third were accepted for plenary presentation at the conference. The best paper of the conference will be invited to appear in Computational Intelligence.
Advances in Artificial Intelligence
This book constitutes the refereed proceedings of the 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 96, held in Toronto, Ontario, Canada, in May 1996. The 35 revised full papers presented in the book were carefully selected by the program committee. Although organized by a national society, AI 96 attracted contributions and participants with a significant geographic diversity. The issues addressed in this volume cover an electic range of current AI topics with a certain emphasis on various aspects of knowledge representation, natural language processing, and learning.
Advances in Knowledge Discovery and Data Mining
This book constitutes the refereed proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2001, held in Hong Kong, China in April 2001. The 38 revised full papers and 22 short papers presented were carefully reviewed and selected from a total of 152 submissions. The book offers topical sections on Web mining, text mining, applications and tools, concept hierarchies, feature selection, interestingness, sequence mining, spatial and temporal mining, association mining, classification and rule induction, clustering, and advanced topics and new methods.
Machine Learning: ECML 2005
The European Conference on Machine Learning (ECML) and the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) were jointly organized this year for the ?fth time in a row, after some years of mutual independence before. After Freiburg (2001), Helsinki (2002), Cavtat (2003) and Pisa (2004), Porto received the 16th edition of ECML and the 9th PKDD in October 3–7. Having the two conferences together seems to be working well: 585 di?erent paper submissions were received for both events, which maintains the high s- mission standard of last year. Of these, 335 were submitted to ECML only, 220 to PKDD only and 30 to both. Such a high volume of scienti?c work ...
Machine Learning: ECML 2001
This book constitutes the refereed proceedings of the 12th European Conference on Machine Learning, ECML 2001, held in Freiburg, Germany, in September 2001. The 50 revised full papers presented together with four invited contributions were carefully reviewed and selected from a total of 140 submissions. Among the topics covered are classifier systems, naive-Bayes classification, rule learning, decision tree-based classification, Web mining, equation discovery, inductive logic programming, text categorization, agent learning, backpropagation, reinforcement learning, sequence prediction, sequential decisions, classification learning, sampling, and semi-supervised learning.
Inductive Logic Programming
Inductive logic programming is a new research area emerging at present. Whilst inheriting various positive characteristics of the parent subjects of logic programming an machine learning, it is hoped that the new area will overcome many of the limitations of its forbears. This book describes the theory, implementations and applications of Inductive Logic Programming.
PRICAI 2006: Trends in Artificial Intelligence
This book constitutes the refereed proceedings of the 9th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2006, held in Guilin, China in August 2006. The book presents 81 revised full papers and 87 revised short papers together with 3 keynote talks. The papers are organized in topical sections on intelligent agents, automated reasoning, machine learning and data mining, natural language processing and speech recognition, computer vision, perception and animation, and more.
