链接开放语料库模型,利用语义网自适应超媒体

Ian R. O’Keeffe, A. O'Connor, P. Cass, S. Lawless, V. Wade
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引用次数: 1

摘要

尽管最近有兴趣将自适应超媒体从封闭语料库领域扩展到网络的开放语料库领域,但目前的许多方法都受到依赖封闭元数据模型存储库的限制。生成大量高质量元数据的需求是一项代价高昂的任务,它会导致高质量元数据的孤岛。由于元数据描述的内容的专有性质和元数据本身的感知价值,这些筒仓通常没有得到充分利用。与此同时,关联开放数据运动正在推广一种实用的方法,使用一套商定的最佳实践,在WWW上公开、共享和连接机器可读的数据和知识。在本文中,我们确定了基于关联开放数据构建个性化系统所产生的潜在问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Linked open corpus models, leveraging the semantic web for adaptive hypermedia
Despite the recent interest in extending Adaptive Hypermedia beyond the closed corpus domain and into the open corpus world of the web, many current approaches are limited by their reliance on closed metadata model repositories. The need to produce large quantities of high quality metadata is an expensive task which results in silos of high quality metadata. These silos are often underutilized due to the proprietary nature of the content described by the metadata and the perceived value of the metadata itself. Meanwhile, the Linked Open Data movement is promoting a pragmatic approach to exposing, sharing and connecting pieces of machine-readable data and knowledge on the WWW using an agreed set of best practices. In this paper we identify the potential issues that arise from building personalization systems based on Linked Open Data.
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