Question routing to user communities
Question routing to user communities
复制标题
问题路由至用户社区
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Barton A. Smith
中科院分区：
文献类型：
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作者：
Aditya Pal;Fei Wang;Michelle X. Zhou;Jeffrey Nichols;Barton A. Smith
在线社区由一群拥有共同兴趣、背景或经验的用户组成，他们的集体目标是为社区成员的福利做出贡献。问答是使社区成员能够在社区边界内交流知识的重要功能。绝大多数社区需要一个良好的问题路由策略，以便将新问题路由到适当关注的社区并得到解决。在本文中，我们考虑将问题路由到正确社区的新问题，并提出一个框架来为问题选择正确的社区集。我们首先使用之前为用户提出的几个特征，并添加一些附加特征，即语言属性和响应倾向，以进行社区建模。然后我们引入两种基于 k 最近邻的聚合算法来计算社区得分。我们展示了如何结合这些分数来推荐社区并在大型现实世界数据集上测试推荐的有效性。
An online community consists of a group of users who share a common interest, background, or experience and their collective goal is to contribute towards the welfare of the community members. Question answering is an important feature that enables community members to exchange knowledge within the community boundary. The overwhelming number of communities necessitates the need for a good question routing strategy so that new questions gets routed to the appropriately focused community and thus get resolved. In this paper, we consider the novel problem of routing questions to the right community and propose a framework to select the right set of communities for a question. We begin by using several prior proposed features for users and add some additional features, namely language attributes and inclination to respond, for community modeling. Then we introduce two k nearest neighbor based aggregation algorithms for computing community scores. We show how these scores can be combined to recommend communities and test the effectiveness of the recommendations over a large real world dataset.