Institution
Dublin City University
Education•Dublin, Ireland•
About: Dublin City University is a education organization based out in Dublin, Ireland. It is known for research contribution in the topics: Machine translation & Laser. The organization has 5904 authors who have published 17178 publications receiving 389376 citations. The organization is also known as: National Institute for Higher Education, Dublin & DCU.
Topics: Machine translation, Laser, Irish, Population, Context (language use)
Papers published on a yearly basis
Papers
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TL;DR: TinyPBC as discussed by the authors is the most efficient implementation of PBC primitives for 8, 16 and 32-bit processors commonly found in sensor nodes and can compute pairings in 1.90s on ATmega128L, 1.27s on MSP430 and 0.14s on PXA27x.
174 citations
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TL;DR: In this paper, the authors show that the existence of sharp, dynamic and new correlations between companies related to the term "corona", outside of pre-existing interrelationships.
173 citations
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TL;DR: In this article, the preparation and properties of reduced graphene oxide (rGO) and graphene nanosheets (GNSs) reinforcement of aluminium matrix nanocomposites (AMCs) are reported.
173 citations
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TL;DR: In this article, the authors draw on the concepts of effectuation, improvisation, prior knowledge and networks to study the early internationalization of new ventures operating in the Irish Shellfish sector.
Abstract: How do entrepreneurs identify foreign market opportunities and how do they identify foreign market(s) and customers? We draw on the concepts of effectuation, improvisation, prior knowledge and networks to study the early internationalization of new ventures operating in the Irish Shellfish sector. We argue that the internationalization process was strongly influenced by two ‘resources to hand’: the entrepreneurs’ idiosyncratic prior knowledge and their prior social and business ties. We observe an effectuation logic and extensive improvisation in the internationalization process of these new ventures.
173 citations
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TL;DR: The working group’s vision for the evolution of digital libraries and the role that personalisation and recommender systems will play are outlined, and a series of research challenges and specific recommendations and research priorities for the field are presented.
Abstract: Widespread use of the Internet has resulted in digital libraries that are increasingly used by diverse communities of users for diverse purposes and in which sharing and collaboration have become important social elements. As such libraries become commonplace, as their contents and services become more varied, and as their patrons become more experienced with computer technology, users will expect more sophisticated services from these libraries. A simple search function, normally an integral part of any digital library, increasingly leads to user frustration as user needs become more complex and as the volume of managed information increases. Proactive digital libraries, where the library evolves from being passive and untailored, are seen as offering great potential for addressing and overcoming these issues and include techniques such as personalisation and recommender systems. In this paper, following on from the DELOS/NSF Working Group on Personalisation and Recommender Systems for Digital Libraries, which met and reported during 2003, we present some background material on the scope of personalisation and recommender systems in digital libraries. We then outline the working group's vision for the evolution of digital libraries and the role that personalisation and recommender systems will play, and we present a series of research challenges and specific recommendations and research priorities for the field.
173 citations
Authors
Showing all 6059 results
Name | H-index | Papers | Citations |
---|---|---|---|
Joseph Wang | 158 | 1282 | 98799 |
David Cameron | 154 | 1586 | 126067 |
David Taylor | 131 | 2469 | 93220 |
Gordon G. Wallace | 114 | 1267 | 69095 |
David A. Morrow | 113 | 598 | 56776 |
G. Hughes | 103 | 957 | 46632 |
David Wilson | 102 | 757 | 49388 |
Muhammad Imran | 94 | 3053 | 51728 |
Haibo Zeng | 94 | 604 | 39226 |
David Lloyd | 90 | 1017 | 37691 |
Vikas Kumar | 89 | 859 | 39185 |
Luke P. Lee | 84 | 413 | 22803 |
James Chapman | 82 | 483 | 36468 |
Muhammad Iqbal | 77 | 961 | 23821 |
Michael C. Berndt | 76 | 228 | 16897 |