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ARTIFICIAL INTELLIGENCE
Artificial Intelligence is a component of Encyclopedia of Technology, Information, and Systems Management Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty Encyclopedias. The Theme on Artificial Intelligence provides the essential aspects and fundamentals of Artificial Intelligence: Definition, Trends, Techniques, and Cases; Logic in Artificial Intelligence (AI); Computational Intelligence; Knowledge Based System Development Tools. It is aimed at the following five major target audiences: University and College Students, Educators, Professional Practitioners, Research Personnel and Policy Analysts, Managers, and Decision Makers.
Artificial Intelligence and Innovations 2007: From Theory to Applications
This book brings together leading research from engineers and practitioners interested in the technical advances, business and industrial applications of intelligent systems. AIAI 2007 is focused on providing insights on how AI can be implemented in real world applications. Topics covered in this volume include: Theoretical Advances in AI; Intelligent Internet Systems: Emerging Technologies and Applications; Intelligent Systems in Electronic Healthcare; AI in Business and Finance.
BNAIC 2016: Artificial Intelligence
This book contains a selection of the best papers that were presented at the 28th edition of the annual Benelux Conference on Artificial Intelligence, BNAIC 2016. The conference took place on November 10-11, 2016, in Hotel Casa 400 in Amsterdam. The conference was jointly organized by the University of Amsterdam and the Vrije Universiteit Amsterdam, under the auspices of the Benelux Association for Artificial Intelligence (BNVKI) and the Dutch Research School for Information and Knowledge Systems (SIKS). The objective of BNAIC is to promote and disseminate recent research developments in Artificial Intelligence, particularly within Belgium, Luxembourg and the Netherlands, although it does not exclude contributions from countries outside the Benelux. The 13 contributions presented in this volume (8 regular papers, 4 student papers, and 1 demonstration paper) were carefully reviewed and selected from 93 submissions. They address various aspects of artificial intelligence such as natural language processing, agent technology, game theory, problem solving, machine learning, human-agent interaction, AI & education, and data analysis.
Advances in Data Mining
This book constitutes the refereed proceedings of the 6th Industrial Conference on Data Mining, ICDM 2006, held in Leipzig, Germany in July 2006. Presents 45 carefully reviewed and revised full papers organized in topical sections on data mining in medicine, Web mining and logfile analysis, theoretical aspects of data mining, data mining in marketing, mining signals and images, and aspects of data mining, and applications such as intrusion detection, and more.
Combinatorial Image Analysis
This volume constitutes the refereed proceedings of the 12th International Workshop on Combinatorial Image Analysis, IWCIA 2008, held in Buffalo, NY, USA, in April 2008. The 28 revised full papers and 10 revised poster papers presented were carefully reviewed and selected from 117 initial submissions. The papers are organized in topical sections on digital geometry and topology, curves and surfaces, combinatorics in digital spaces: lattice polygons, polytopes, tilings, and patterns, image representation, segmentation, grouping, and reconstruction, applications of computational geometry, integer and linear programming to image analysis, fuzzy and stochastic image analysis, parallel architectures and algorithms, grammars and models for image or scene analysis, as well as discrete tomography, medical imaging, and biometrics.
Pattern Recognition Applications and Methods
This book contains revised and extended versions of selected papers from the 5th International Conference on Pattern Recognition, ICPRAM 2016, held in Rome, Italy, in February 2016. The 13 full papers were carefully reviewed and selected from 125 initial submissions and describe up-to-date applications of pattern recognition techniques to real-world problems, interdisciplinary research, experimental and/or theoretical studies yielding new insights that advance pattern recognition methods.
Machine Learning and Knowledge Discovery in Databases
The three volume proceedings LNAI 10534 – 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions; there are 47 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: anomaly detection; computer vision; ensembles and meta learning; feature selection and extraction; kernel methods; learning and optimization, matrix and tensor factorization; networks and graphs; neural networks and deep learning. Part II: pattern and sequence mining; privacy and security; probabilistic models and methods; recommendation; regression; reinforcement learning; subgroup discovery; time series and streams; transfer and multi-task learning; unsupervised and semisupervised learning. Part III: applied data science track; nectar track; and demo track.
Advances in Knowledge Discovery and Data Mining
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.
