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Welcome to the largest bibliographic database dedicated to Economics and available freely on the Internet. This site is part of a large volunteer effort to enhance the free dissemination of research in Economics, RePEc, which includes bibliographic metadata from over 1,800 participating archives, including all the major publishers and research outlets. IDEAS is just one of several services that use RePEc data. Authors are invited to register with RePEc to create an online profile. Then, anyone finding some of your research here can find your latest contact details and a listing of your other research. You will also receive a monthly mailing about the popularity of your works, your ranking and newly found citations. Besides that IDEAS provides software and public accessible data from Federal Reserve Bank.
HunCLARIN is a strategic research infrastructure of Hungary’s leading knowledge centres involved in R&D in speech- and language processing. It contains linguistic resources and tools that form the basis of research. The infrastructure has obtained an “SKI” qualification (Strategic Research Infrastructure) in 2010, and has been significantly expanded since. Currently comprising 36 members, the infrastructure includes several general- and specific-purpose text corpora, different language processing tools and analysers, linguistic databases as well as ontologies. RIL HAS was a co-founder of the European CLARIN project, which aims at supporting humanities and social sciences research with the help of language technology and by making digital linguistic resources more easily available. In accordance with these goals HunClarin makes the research infrastructures developed by the respective centres directly accessible for researchers through a common network entry point. A general goal of the infrastructure is to realise the interoperability of the collected research infrastructures and to enable comparing the performance of the respective alternatives and to coordinate different foci in R&D. The coordinator and contact person of the infrastructure is Tamás Váradi, RIL HAS.
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.