一个在专家调查中将证据语境化的框架

Rodrigo Gonçalves, C. Dorneles
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引用次数: 0

摘要

专家发现传统上与信息检索的研究主题有关,通常被认为是“特定组织内的专业知识检索”。这项任务涉及到在某一专业领域找到一位专家。尽管文献中有一些有趣的建议,但它们并没有考虑到特定专业知识所处的环境。这篇博士论文介绍了一个框架的概念,该框架按时间顺序将专家发现的搜索结果语境化。我们的动机是提供更准确的搜索过程结果,这些结果与寻找特定主题的专家有关,将专业/学术活动的专业知识背景化,一个开放的研究主题。在本文中,我们介绍了我们正在开发的框架的主要概念及其操作的总体概述。目前,我们正在使用拿铁平台作为数据源,为此我们开发了一个流程来提取专业证据,并由Crossref数据库提供支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experion: A framework for contextualizing evidence in expert finding
Expert finding is traditionally related to a subject of research in information retrieval and, often, is taken to mean "expertise retrieval within a specific organization". The task involves finding an expert in an expertise topic. Even though there are interesting proposals in the literature, they do not consider the context in which a given expertise is bound. This Ph.D. thesis introduces the concept of a framework that chronologically contextualizes search results in expert finding. Our motivation is to provide more accurate results of search processes related to finding experts in a given topic, contextualizing the expertise on professional/academic activities, an open research topic. In this paper, we present the main concepts of the framework we are developing and a general overview of its operation. At the moment, we are using the Lattes platform as a data source, for which we developed a process to extract expertise evidence, supported by the Crossref database.
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