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A General Architecture to Enhance Wiki Systems with Natural Language Processing Techniques

机译:使用自然语言处理技术增强Wiki系统的通用体系结构

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摘要

Wikis are web-based software applications that allow users to collaboratively create and edit web page content, through a Web browser using a simplified syntax. The ease-of-use and “open” philosophy of wikis has brought them to the attention of organizations and online communities, leading to a wide-spread adoption as a simple and “quick” way of collaborative knowledge management. However, these characteristics of wiki systems can act as a double-edged sword: When wiki content is not properly structured, it can turn into a “tangle of links”, making navigation, organization and content retrieval difficult for their end-users.udSince wiki content is mostly written in unstructured natural language, we believe that existing state-of-the-art techniques from the Natural Language Processing (NLP) and Semantic Computing domains can help mitigating these common problems when using wikis and improve their users’ experience by introducing new features. The challenge, however, is to find a solution for integrating novel semantic analysis algorithms into the multitude of existing wiki systems, without the need for modifying their engines. In this research work, we present a general architecture that allows wiki systems to benefit from NLP services made available through the Semantic Assistants framework – a service-oriented architecture for brokering NLP pipelines as web services. Our main contributions in this thesis include an analysis of wiki engines, the development of collaboration patterns be- tween wikis and NLP, and the design of a cohesive integration architecture. As a concrete application, we deployed our integration to MediaWiki – the powerful wiki engine behind Wikipedia – to prove its practicability. Finally, we evaluate the usability and efficiency of our integration through a number of user studies we performed in real-world projects from various domains, including cultural heritage data management, software requirements engineering, and biomedical literature curation.
机译:Wiki是基于Web的软件应用程序,它允许用户使用简化的语法通过Web浏览器来协作创建和编辑Web网页内容。 Wiki的易用性和“开放”理念引起了组织和在线社区的注意,并导致其被广泛采用为协作知识管理的一种简单且“快速”的方式。但是,Wiki系统的这些特征可以充当一把双刃剑:如果Wiki内容的结构不正确,则可能变成“链接纠结”,从而使最终用户难以进行导航,组织和内容检索。 ud由于Wiki内容主要是用非结构化自然语言编写的,因此我们认为,自然语言处理(NLP)和语义计算领域的现有最新技术可以帮助缓解使用Wiki时遇到的常见问题,并改善用户体验通过引入新功能。然而,挑战在于找到一种解决方案,以将新颖的语义分析算法集成到众多现有的Wiki系统中,而无需修改其引擎。在这项研究工作中,我们提出了一种通用体系结构,该体系结构允许Wiki系统从通过语义助手框架提供的NLP服务中受益–一种面向服务的体系结构,用于将NLP管道作为Web服务进行中介。我们在本文中的主要贡献包括对Wiki引擎的分析,Wiki与NLP之间协作模式的开发以及内聚集成体系结构的设计。作为一个具体的应用程序,我们将集成部署到MediaWiki(Wikipedia背后的强大Wiki引擎)中,以证明其实用性。最后,我们通过在不同领域的现实世界项目中进行的大量用户研究,评估了集成的可用性和效率,这些领域包括文化遗产数据管理,软件需求工程和生物医学文献管理。

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  • 作者

    Sateli Bahar;

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  • 年度 2012
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  • 原文格式 PDF
  • 正文语种 en
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