{"title":"Competition-based networks for expert finding","authors":"Çigdem Aslay, Neil O'Hare, L. Aiello, A. Jaimes","doi":"10.1145/2484028.2484183","DOIUrl":null,"url":null,"abstract":"Finding experts in question answering platforms has important applications, such as question routing or identification of best answers. Addressing the problem of ranking users with respect to their expertise, we propose Competition-Based Expertise Networks (CBEN), a novel community expertise network structure based on the principle of competition among the answerers of a question. We evaluate our approach on a very large dataset from Yahoo! Answers using a variety of centrality measures. We show that it outperforms state-of-the-art network structures and, unlike previous methods, is able to consistly outperform simple metrics like best answer count. We also analyse question answering forums in Yahoo! Answers, and show that they can be characterised by factual or subjective information seeking behavior, social discussions and the conducting of polls or surveys. We find that the ability to identify experts greatly depends on the type of forum, which is directly reflected in the structural properties of the expertise networks.","PeriodicalId":178818,"journal":{"name":"Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"43","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2484028.2484183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 43
Abstract
Finding experts in question answering platforms has important applications, such as question routing or identification of best answers. Addressing the problem of ranking users with respect to their expertise, we propose Competition-Based Expertise Networks (CBEN), a novel community expertise network structure based on the principle of competition among the answerers of a question. We evaluate our approach on a very large dataset from Yahoo! Answers using a variety of centrality measures. We show that it outperforms state-of-the-art network structures and, unlike previous methods, is able to consistly outperform simple metrics like best answer count. We also analyse question answering forums in Yahoo! Answers, and show that they can be characterised by factual or subjective information seeking behavior, social discussions and the conducting of polls or surveys. We find that the ability to identify experts greatly depends on the type of forum, which is directly reflected in the structural properties of the expertise networks.
在问答平台中寻找专家具有重要的应用,例如问题路由或最佳答案的识别。针对用户的专业知识排序问题,我们提出了基于竞争的专业知识网络(competition - based expertise Networks,简称CBEN),这是一种基于问题答题者之间竞争原则的新型社区专业知识网络结构。我们用雅虎的一个非常大的数据集来评估我们的方法。使用各种中心性度量的答案。我们表明,它优于最先进的网络结构,并且与以前的方法不同,它能够始终优于简单的指标,如最佳答案计数。我们还分析了雅虎的问答论坛。答案,并表明它们可以以事实或主观信息寻求行为,社会讨论和进行民意调查或调查为特征。我们发现识别专家的能力在很大程度上取决于论坛的类型,这直接反映在专家网络的结构属性上。