Merging and Revision of Uncertain Knowledge and Information from Multiple Sources - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Merging and Revision of Uncertain Knowledge and Information from Multiple Sources write by Jianbing Ma. This book was released on 2009. Merging and Revision of Uncertain Knowledge and Information from Multiple Sources available in PDF, EPUB and Kindle.
Merging and Revision of Uncertain Knowledge and Information from Multiple Sources
Merging and Revision of Uncertain Knowledge and Information from Multiple Sources - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Merging and Revision of Uncertain Knowledge and Information from Multiple Sources write by J. Ma. This book was released on 2010. Merging and Revision of Uncertain Knowledge and Information from Multiple Sources available in PDF, EPUB and Kindle.
Fusion and Revision of Uncertain Information from Multiple Sources
Fusion and Revision of Uncertain Information from Multiple Sources - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fusion and Revision of Uncertain Information from Multiple Sources write by Jianbing Ma. This book was released on 2012. Fusion and Revision of Uncertain Information from Multiple Sources available in PDF, EPUB and Kindle. In the last three decades, information sources, especially the internet, are growing up more and more rapidly. Thus, people feel very comfortable to find any information they want from these sources. Experiences and observations show that when an agent wants to get any information, it usually gets a large amount from various online sources. However, in contrast to the easiness of obtaining the information, processing the information from heterogeneous sources becomes a difficult job. The main problem is that these pieces of information from different sources are usually inconsistent, and even the information itself contains uncertainty. Therefore, it becomes an important issue to utilize these pieces of information in a consistent and rational manner. This book concentrates on using merging and revision operations to deal with these situations.
Information Processing and Management of Uncertainty in Knowledge-Based Systems
Information Processing and Management of Uncertainty in Knowledge-Based Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Information Processing and Management of Uncertainty in Knowledge-Based Systems write by Eyke Hüllermeier. This book was released on 2010-06-25. Information Processing and Management of Uncertainty in Knowledge-Based Systems available in PDF, EPUB and Kindle. The International Conference on Information Processing and Management of - certainty in Knowledge-Based Systems, IPMU, is organized every two years with the aim of bringing together scientists working on methods for the management of uncertainty and aggregation of information in intelligent systems. Since 1986, this conference has been providing a forum for the exchange of ideas between th theoreticians and practitioners working in these areas and related ?elds. The 13 IPMU conference took place in Dortmund, Germany, June 28–July 2, 2010. This volume contains 79 papers selected through a rigorous reviewing process. The contributions re?ect the richness of research on topics within the scope of the conference and represent several important developments, speci?cally focused on theoretical foundations and methods for information processing and management of uncertainty in knowledge-based systems. We were delighted that Melanie Mitchell (Portland State University, USA), Nihkil R. Pal (Indian Statistical Institute), Bernhard Sch ̈ olkopf (Max Planck I- titute for Biological Cybernetics, Tubing ̈ en, Germany) and Wolfgang Wahlster (German Research Center for Arti?cial Intelligence, Saarbruc ̈ ken) accepted our invitations to present keynote lectures. Jim Bezdek received the Kamp ́ede F ́ eriet Award, granted every two years on the occasion of the IPMU conference, in view of his eminent research contributions to the handling of uncertainty in clustering, data analysis and pattern recognition.
Federal Statistics, Multiple Data Sources, and Privacy Protection
Federal Statistics, Multiple Data Sources, and Privacy Protection - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Federal Statistics, Multiple Data Sources, and Privacy Protection write by National Academies of Sciences, Engineering, and Medicine. This book was released on 2018-01-27. Federal Statistics, Multiple Data Sources, and Privacy Protection available in PDF, EPUB and Kindle. The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.
