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This book constitutes the refereed proceedings of the workshops held at the 17th Asia-Pacific Web Conference, APWeb 2015, in Guangzhou, China, in September 2015. The 15 full papers were carefully reviewed and selected from various submissions. The volume presents the papers that have been accepted for the following workshops: Big Data Applications in Telecoms, BDAT 2015, Big Social Data, BSD 2015, and Web Data Mining and Applications, WDMA 2015. The papers cover various issues in the area of the World Wide Web with the underlying technologies and applications.
This book constitutes the refereed proceedings of the 17th Asia-Pacific Conference APWeb 2015 held in Guangzhou, China, in September 2015. The 67 full papers and presented together with 3 industrial track papers and 7 demonstration track papers were carefully reviewed and selected from 146 submissions. The papers cover a wide spectrum of Web-related data management problems, and provide a thorough view on the rapid advances of technical solutions.
The idea behind TSP was conceived by Austrian mathematician Karl Menger in mid 1930s who invited the research community to consider a problem from the everyday life from a mathematical point of view. A traveling salesman has to visit exactly once each one of a list of m cities and then return to the home city. He knows the cost of traveling from any city i to any other city j. Thus, which is the tour of least possible cost the salesman can take? In this book the problem of finding algorithmic technique leading to good/optimal solutions for TSP (or for some other strictly related problems) is considered. TSP is a very attractive problem for the research community because it arises as a natural subproblem in many applications concerning the every day life. Indeed, each application, in which an optimal ordering of a number of items has to be chosen in a way that the total cost of a solution is determined by adding up the costs arising from two successively items, can be modelled as a TSP instance. Thus, studying TSP can never be considered as an abstract research with no real importance.
This book constitutes the refereed proceedings of the International Conference on Intelligent Computing, ICIC 2006, held in Kunming, China, in August 2006. The book presents 165 revised full papers, carefully reviewed. Topics covered include ant colony optimization, particle swarm optimization, swarm intelligence, autonomy-oriented computing, quantum and molecular computations, biological and DNA computing, intelligent computing in bioinformatics, intelligent computing in computational biology and drug design, computational genomics and proteomics, and more.
Solving problems with deep neural networks typically relies on massive amounts of labeled training data to achieve high performance/b>. While in many situations huge volumes of unlabeled data can be and often are generated and available, the cost of acquiring data labels remains high. Transfer learning (TL), and in particular domain adaptation (DA), has emerged as an effective solution to overcome the burden of annotation, exploiting the unlabeled data available from the target domain together with labeled data or pre-trained models from similar, yet different source domains. The aim of this book is to provide an overview of such DA/TL methods applied to computer vision, a field whose popula...
Part of a four-volume set, this book constitutes the refereed proceedings of the 7th International Conference on Computational Science, ICCS 2007, held in Beijing, China in May 2007. The papers cover a large volume of topics in computational science and related areas, from multiscale physics to wireless networks, and from graph theory to tools for program development.
This book and its companion volume, LNCS vols. 7331 and 7332, constitute the Proceedings of the Third International conference on Swarm Intelligence, ICSI 2012, held in Shenzhen, China in June 2012. The 145 full papers presented were carefully reviewed and selected from 247 submissions. The papers are organized in 27 cohesive sections covering all major topics of swarm intelligence research and developments.
MACHINE LEARNING AND DATA SCIENCE Written and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia. Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifesty...
This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybers...
This book constitutes the refereed proceedings of the 9th International Conference on Intelligent Computing, ICIC 2013, held in Nanning, China, in July 2013. The 192 revised full papers presented in the three volumes LNCS 7995, LNAI 7996, and CCIS 375 were carefully reviewed and selected from 561 submissions. The papers in this volume (CCIS 375) are organized in topical sections on Neural Networks; Systems Biology and Computational Biology; Computational Genomics and Proteomics; Knowledge Discovery and Data Mining; Evolutionary Learning and Genetic Algorithms; Machine Learning Theory and Methods; Biomedical Informatics Theory and Methods; Particle Swarm Optimization and Niche Technology; Uns...