首页> 外文期刊>International journal of intelligent systems in accounting, finance & management >MANAGEMENT OF KNOWLEDGE SOURCES SUPPORTED BY DOMAIN ONTOLOGIES: BUILDING AND CONSTRUCTION CASE STUDY
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MANAGEMENT OF KNOWLEDGE SOURCES SUPPORTED BY DOMAIN ONTOLOGIES: BUILDING AND CONSTRUCTION CASE STUDY

机译:域本体论支持的知识源管理:建筑和施工案例研究

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This paper introduces a novel conceptual framework to support the creation of knowledge representations based on enriched semantic vectors, using the classical vector space model approach extended with ontological support. This work is focused on collaborative engineering projects where knowledge plays a key role in the process. Collaboration is the arena, engineering projects are the target and knowledge is the currency used to provide harmony into the arena since it can potentially support innovation and, hence, a successful collaboration. The test bed for the assessment of the approach comes from the Building and Construction sector, which is challenged with significant problems for exchanging, sharing and integrating information among actors. Semantic gaps or lack of meaning definition at the conceptual and technical levels, for example, are problems fundamentally originated through the employment of representations to map the 'world' into models in an endeavour to anticipate other actors' views, vocabulary and even motivations. One of the primary research challenges addressed in this work relates to the process of formalization and representation of document contents, where most existing approaches are limited and only take into account the explicit, word-based information in the document. The research described in this paper explores how traditional knowledge representations can be enriched through incorporation of implicit information derived from the complex relationships (semantic associations) modelled by domain ontologies with the addition of information presented in documents, by providing a baseline for facilitating knowledge interpretation and sharing between humans and machines. Preliminary results were collected using a clustering algorithm for document classification, which indicates that the proposed approach does improve the precision and recall of classifications. Future work and open issues are also discussed.
机译:本文介绍了一种新颖的概念框架,该框架使用在本体支持下扩展的经典向量空间模型方法来支持基于丰富语义向量的知识表示的创建。这项工作专注于协作工程项目,其中知识在此过程中起着关键作用。协作是竞技场,工程项目是目标,知识是在竞技场中提供和谐的货币,因为它可以潜在地支持创新并因此获得成功的协作。评估方法的测试平台来自建筑和建筑部门,在参与者之间交换,共享和集成信息方面存在重大问题,因此面临挑战。例如,在概念和技术层面上的语义鸿沟或缺乏意义的定义,这些问题根本上源于使用表象将“世界”映射到模型中,以期预期其他参与者的观点,词汇甚至动机。这项工作中解决的主要研究挑战之一是文档内容的形式化和表示过程,其中大多数现有方法都受到限制,并且仅考虑了文档中基于单词的明确信息。本文中描述的研究探索了如何通过引入基础知识来促进知识的解释和融合,这些隐含信息是通过合并由领域本体建模的复杂关系(语义关联)衍生的隐式信息,并添加文档中提供的信息来丰富的。人与机器之间的共享。使用聚类算法对文档分类收集了初步结果,这表明所提出的方法确实提高了分类的准确性和召回率。还讨论了未来的工作和未解决的问题。

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