非监督学习辅助下的非政府组织志愿者分配

Carlos M. M. Bezerra, Danilo R. B. Araújo, V. Macário
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引用次数: 1

摘要

目前,推荐系统已成功应用于教育、电子商务、旅游、在线娱乐等多个应用领域。然而,有一些应用可以通过推荐系统得到帮助,但之前还没有研究为这些应用提出合适的建议。在本文中,我们开展了一项有关使用推荐系统技术来帮助非政府组织(ngo)的志愿者分配的研究。我们通过使用两种评估聚类的度量来评估两种不同的聚类算法。当算法被应用于创建来自巴西非政府组织的不同志愿者群体时,我们通过考虑志愿者概况来评估算法的有效性。根据我们的分析,非监督学习有望建立一个更完整的支持决策系统,以帮助非政府组织管理与志愿者分配相关的事务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Allocation of Volunteers in Non-governmental Organizations Aided by Non-supervised Learning
Nowadays recommender systems are successfully used in several application domains such in the educational field, e-commerce, tourism, online entertainment, and so on. However, there are some applications that could be aided by recommender systems but no previous study has already been developed to propose a suitable proposal for such applications. In this paper we develop a study related to the use of recommender systems techniques to aid the volunteers allocation in Non-Governmental Organizations (NGOs). We evaluated two different clustering algorithms by using two measures for evaluation of clusters. We evaluate the effectiveness of the algorithms when they are applied to create different groups of volunteers from Brazilian NGOs by considering the volunteering profile. According to our analysis, the non-supervised learning is promising to build a more complete support decision system to aid the management of NGOs related to volunteers allocation.
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