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A multi-disciplinar recommender system to advice research resources in University Digital Libraries

机译:一个多学科的推荐系统,为大学数字图书馆的研究资源提供建议

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The Web is one of the most important information media and it is influencing in the development of other media, as for example, newspapers, journals, books, and libraries. In this paper, we analyze the logical extensions of traditional libraries in the Information Society. In Information Society people want to communicate and collaborate. So, libraries must develop services for connecting people together in information environments. Then, the library staff need automatic techniques to facilitate so that a great number of users can access to a great number of resources. Recommender systems are tools whose objective is to evaluate and filter the great amount of information available on the Web to assist the users in their information access processes. We present a model of a fuzzy linguistic recommender system to help the University Digital Libraries users to access for their research resources. This system recommends researchers specialized and complementary resources in order to discover collaboration possibilities to form multi-disciplinar groups. In this way, this system increases social collaboration possibilities in a university framework and contributes to improve the services provided by a University Digital Library.
机译:Web是最重要的信息媒体之一,它正在影响其他媒体的发展,例如报纸,期刊,书籍和图书馆。在本文中,我们分析了信息社会中传统图书馆的逻辑扩展。在信息社会中,人们希望交流和合作。因此,图书馆必须开发服务以在信息环境中将人们联系在一起。然后,图书馆工作人员需要自动技术来促进便利,以便大量用户可以访问大量资源。推荐系统是工具,其目的是评估和过滤Web上可用的大量信息,以帮助用户进行信息访问过程。我们提出一种模糊语言推荐系统的模型,以帮助大学数字图书馆用户访问其研究资源。该系统向研究人员推荐专业的补充资源,以发现形成多学科小组的协作可能性。这样,该系统增加了大学框架内的社交协作可能性,并有助于改善大学数字图书馆提供的服务。

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