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Titlebook: Artificial Intelligence Applications and Innovations; 6th IFIP WG 12.5 Int Harris Papadopoulos,Andreas S. Andreou,Max Bramer Conference pro

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期刊全称Artificial Intelligence Applications and Innovations
期刊简称6th IFIP WG 12.5 Int
影响因子2023Harris Papadopoulos,Andreas S. Andreou,Max Bramer
视频video
发行地址State-of-the-art research.Fast-track conference proceedings.Unique visibility
学科分类IFIP Advances in Information and Communication Technology
图书封面Titlebook: Artificial Intelligence Applications and Innovations; 6th IFIP WG 12.5 Int Harris Papadopoulos,Andreas S. Andreou,Max Bramer Conference pro
影响因子The abundance of information and increase in computing power currently enable researchers to tackle highly complicated and challenging computational problems. Solutions to such problems are now feasible using advances and innovations from the area of Artificial Intelligence. The general focus of the AIAI conference is to provide insights on how Artificial Intelligence may be applied in real-world situations and serve the study, analysis and modeling of theoretical and practical issues. This volume contains papers selected for presentation at the 6th IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI 2010) and held in Larnaca, Cyprus, during October 6–7, 2010. IFIP AIAI 2010 was co-organized by the University of Cyprus and the Cyprus University of Technology and was sponsored by the Cyprus University of Technology, Frederick University and the Cyprus Tourism Organization. AIAI 2010 is the official conference of the WG12.5 “Artificial Intel- gence Applications” working group of IFIP TC12, the International Federation for Information Processing Technical Committee on Artificial Intelligence (AI). AIAI is a conference that grows in significance every year att
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978-3-642-42361-1IFIP International Federation for Information Processing 2010
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Artificial Intelligence Applications and Innovations978-3-642-16239-8Series ISSN 1868-4238 Series E-ISSN 1868-422X
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Sule Anjomshoae,Kary Främling,Amro Najjarimited the application of AI techniques in many real world applications. This talk provides an insight into applications of AI techniques in software engineering and how innovative application of AI can assist in achieving ever competitive and firm schedules for software development projects as well
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Tobias Ahlbrecht,Michael Winikofflized recommendations. The most common and accurate approaches to CF are based on latent factor models. Latent factor models can tackle two fundamental problems of CF, data sparsity and scalability and have received considerable attention in recent literature. In this work, we present an optimal sca
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Sule Anjomshoae,Kary Främling,Amro Najjarficant relevant properties. We adapt these data using a Bayesian model that creates normalization conditions to a well fitted artificial neural network. We separate the method in two stages: first implementing the data variable in a functional multi-factorial normalization analysis using a normalizi
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