基于知识检索的自发性社会网络专家用户发现方法

Gustavo Freitas, C. Costa, J. Barbosa, R. Righi, A. Yamin
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引用次数: 1

摘要

如今,我们可以观察到,在社交网络上寻找答案是一项艰巨而耗时的任务。本文的主要贡献是创建了一个模型和算法,允许用户使用名为Mingle的自发社交网络找到问题的答案。该算法使用基于Mingle本体的知识库来寻找专家用户。要实现这一目标,需要采取两个重要步骤:更新Mingle本体以支持面向用户的专业知识,并为给定算法创建详细的模型。该模型是考虑了其他三种类似的应用和算法而创建的。此外,我们还使用了语义web框架。最后,使用现实场景进行评估,以评估所创建的算法是否满足初始目标。
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Expert user discovery in a spontaneous social network an approach using knowledge retrieval
Nowadays, we can observe that finding answers on social networks is a hard and time-consuming task. The main contribution of this article is the creation of a model and algorithm that allows users to find answers to their questions using a spontaneous social network called Mingle. This algorithm uses the Mingle ontology-based knowledge base to find expert users. To achieve this, two important steps are taken: Mingle ontology is updated to support user-oriented expertise and a detailed model is created for the given algorithm. This model was created considering other three similar applications and algorithms. Moreover, we used a semantic web framework. In the end, an evaluation using real-life scenarios is applied to evaluate if the created algorithm meets the initial goals.
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