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  • e-book 
    Pattern Recognition

    Pattern Recognition

    Pattern recognition, despite its relatively short history, has already found practical application in many areas of human activity. Systems of pattern recognition usually support people in performing tasks related to ensuring security, including access to premises and devices, detection of unusual changes (e.g. in medicine, cartography, geology), diagnosing technical conditions of devices, and many others. Nevertheless, pattern recognition is probably the most developing area because of the great demand for such solutions in the different areas of our lives. In this book we have collected the experience of scientists from different parts of the world who have researched diverse areas connected directly or indirectly with pattern recognition. We hope that this book will be a treasure trove of knowledge and inspiration for further research in the field of pattern recognition.

    Subjects:
    Electronic and Information Engineering and Computing
    Keywords:
    Pattern recognition systems Pattern perception Image processing
    Resource Type:
    e-book
     
  • Others 
    Pandas

    Pandas

    Solve short hands-on challenges to perfect your data manipulation skills.

    Subjects:
    Computing
    Keywords:
    Python (Computer program language) Electronic data processing Information visualization
    Resource Type:
    Others
     
  • Presentation 
    Optimizing Debt Collections Using Constrained Reinforcement Learning

    Optimizing Debt Collections Using Constrained Reinforcement Learning

    This video was recorded at 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Washington 2010. The problem of optimally managing the collections process by taxation authorities is one of prime importance, not only for the revenue it brings but also as a means to administer a fair taxing system. The analogous problem of debt collections management in the private sector, such as banks and credit card companies, is also increasingly gaining attention. With the recent successes in the applications of data analytics and optimization to various business areas, the question arises to what extent such collections processes can be improved by use of leading edge data modeling and optimization techniques. In this paper, we propose and develop a novel approach to this problem based on the framework of constrained Markov Decision Process (MDP), and report on our experience in an actual deployment of a tax collections optimization system at New York State Department of Taxation and Finance (NYS DTF).

    Subjects:
    Management and Computing
    Keywords:
    Markov processes -- Mathematical models Debt -- Management
    Resource Type:
    Presentation
     
    OER
  • Presentation 
    OntoNaviERP: Ontology-supported Navigation in ERP Software Documentation

    OntoNaviERP: Ontology-supported Navigation in ERP Software Documentation

    This video was recorded at 7th International Semantic Web Conference (ISWC), Karlsruhe 2008. The documentation of Enterprise Research Planning (ERP) systems is usually (1) extremely large and (2) combines various views from the business and the technical implementation perspective. Also, a very specific vocabulary has evolved, in particular in the SAP domain (e.g. SAP Solution Maps or SAP software module names). This vocabulary is not clearly mapped to business management terminology and concepts. It is a well-known problem in practice that searching in SAP ERP documentation is difficult, because it requires in-depth knowledge of a large and proprietary terminology. We propose to use ontologies and automatic annotation of such large HTML software documentation in order to improve the usability and accessibility, namely of ERP help files. In order to achieve that, we have developed an ontology and prototype for SAP ERP 6.0. Our approach integrates concepts and lexical resources from (1) business management terminology, (2) SAP business terminology, (3) SAP system terminology, and (4) Wordnet synsets. We use standard GATE/KIM technology to annotate SAP help documentation with respective references to our ontology. Eventually, our approach consolidates the knowledge contained in the SAP help functionality at a conceptual level. This allows users to express their queries using a terminology they are familiar with, e.g. referring to general management terms. Despite a widely automated ontology construction process and a simplistic annotation strategy with minimal human intervention, we experienced convincing results. For an average query linked to an action and a topic, our technology returns more than 3 relevant resources, while a naïve term-based search returns on average only about 0.2 relevant resources.

    Subjects:
    Management and Computing
    Keywords:
    Enterprise resource planning Software documentation Ontologies (Information retrieval)
    Resource Type:
    Presentation
     
    OER
  • e-book 
    New Advances in Machine Learning

    New Advances in Machine Learning

    The purpose of this book is to provide an up-to-date and systematical introduction to the principles and algorithms of machine learning. The definition of learning is broad enough to include most tasks that we commonly call “learning” tasks, as we use the word in daily life. It is also broad enough to encompass computers that improve from experience in quite straightforward ways. The book will be of interest to industrial engineers and scientists as well as academics who wish to pursue machine learning. The book is intended for both graduate and postgraduate students in fields such as computer science, cybernetics, system sciences, engineering, statistics, and social sciences, and as a reference for software professionals and practitioners. The wide scope of the book provides a good introduction to many approaches of machine learning, and it is also the source of useful bibliographical information.

    Course related:
    COMP4432 Machine Learning
    Subjects:
    Computing
    Keywords:
    Machine learning
    Resource Type:
    e-book
     
  • Others 
    Natural Language Processing

    Natural Language Processing

    Distinguish yourself by learning to work with text data.

    Subjects:
    Computing
    Keywords:
    Python (Computer program language) Natural language processing (Computer science)
    Resource Type:
    Others
     
  • e-book 
    National Academies Press (Computers and Information Technology)

    National Academies Press (Computers and Information Technology)

    Covers over 5,000 reports published by the National Academies Press for the National Academy of Sciences, National Academy of Engineering, Institute of Medicine and National Research Council in the US.

    Subjects:
    Computing
    Keywords:
    Computer science Information technology
    Resource Type:
    e-book
     
  • e-book 
    Modern Information Systems

    Modern Information Systems

    The development of modern information systems is a demanding task. New technologies and tools are designed, implemented and presented in the market on a daily bases. User needs change dramatically fast and the IT industry copes to reach the level of efficiency and adaptability for its systems in order to be competitive and up-to-date. Thus, the realization of modern information systems with great characteristics and functionalities implemented for specific areas of interest is a fact of our modern and demanding digital society and this is the main scope of this book. Therefore, this book aims to present a number of innovative and recently developed information systems. It is titled "Modern Information Systems" and includes 8 chapters. This book may assist researchers on studying the innovative functions of modern systems in various areas like health, telematics, knowledge management, etc. It can also assist young students in capturing the new research tendencies of the information systems' development.

    Subjects:
    Environmental Sciences and Computing
    Keywords:
    Medical informatics Knowledge management Management information systems
    Resource Type:
    e-book
     
  • Presentation 
    Media Stream

    Media Stream

    This video was recorded at COIN / PlanetData Winter School on Knowledge Technologies for Complex Business Environments, Ljubljana 2011. Organized by COIN FP7 Integrated Project and PlanetData FP7 Network of Excellence, the school seeks to bring together students, scholars and researchers from industry in order to foster collaboration and interoperability with innovative services and project large-scale data management in business environments. The main topics of the winter school are: Interoperability and collaboration models and solutions, Enterprise interoperability and collaboration services, Innovative knowledge and semantically powered technologies, Knowledge process and context modelling, Pro-active knowledge tools, Large scale analytics and reasoning tools, Business cases and real case studies. Detailed information can be found here.

    Subjects:
    Management and Computing
    Keywords:
    Data mining Real-time data processing
    Resource Type:
    Presentation
     
    OER
  • MOOC 
    Machine Learning Specialization

    Machine Learning Specialization

    The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications.
    This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.
    This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012.
    It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start.

    Course related:
    AAE5103 Artificial Intelligence in Aviation Industry
    Subjects:
    Computing
    Keywords:
    Machine learning Artificial intelligence
    Resource Type:
    MOOC