Data Augmentation(DA)插补法是最常用的MCMC多重插补法之一。利用模拟方法研究基于DA插补法的线性回归模型的系数估计值,分析估计值的统计性质受无回答机制、无回答率和插补重数的影响。模拟结果显示:在完全随机无回答机制下,选择较小...Data Augmentation(DA)插补法是最常用的MCMC多重插补法之一。利用模拟方法研究基于DA插补法的线性回归模型的系数估计值,分析估计值的统计性质受无回答机制、无回答率和插补重数的影响。模拟结果显示:在完全随机无回答机制下,选择较小插补重数常常会得到较好的回归系数估计值;在随机无回答机制下,随着无回答率增大而选择更大插补重数往往会得到更好的回归系数估计值;在非随机无回答机制下,选择更大插补重数并不一定总会得到更好的回归系数估计值。展开更多
Community Question Answering （CQA） websites have greatly facilitated users＇ lives, with an increasing number of people seeking help and exchanging ideas on the Internet. This newlymerged community features two char...Community Question Answering （CQA） websites have greatly facilitated users＇ lives, with an increasing number of people seeking help and exchanging ideas on the Internet. This newlymerged community features two characteristics： social relations and an ask-reply mechanism. As users＇ behaviours and social statuses play a more important role in CQA services than traditional answer retrieving websites, researchers＇ concerns have shifted from the need to passively find existing answers to actively seeking potential reply providers that may give answers in the near future. We analyse datasets derived from an online CQA system named ＂Quora＂, and observed that compared with traditional question answering services, users tend to contribute replies rather than questions for help in the CQA system. Inspired by the findings, we seek ways to evaluate the users＇ ability to offer prompt and reliable help, taking into account activity, authority and social reputation char- acteristics. We propose a hybrid method that is based on a Question-User network and social network using optimised PageRank algorithm. Experimental results show the efficiency of the proposed method for ranking potential answer-providers.展开更多
基金supported by the Fundamental Research Funds for the Central Universitiesthe National Natural Science Foundation of China under Grant No.61271041+2 种基金the National Basic Research Program of China (973 Program) under Grant No.2009CB320504the iCore Integrated Project under Grant No.287708the National Scienceand Technology Major Project under Grants No.2012ZX03005008-001,No.2012ZX03002008
文摘Community Question Answering （CQA） websites have greatly facilitated users＇ lives, with an increasing number of people seeking help and exchanging ideas on the Internet. This newlymerged community features two characteristics： social relations and an ask-reply mechanism. As users＇ behaviours and social statuses play a more important role in CQA services than traditional answer retrieving websites, researchers＇ concerns have shifted from the need to passively find existing answers to actively seeking potential reply providers that may give answers in the near future. We analyse datasets derived from an online CQA system named ＂Quora＂, and observed that compared with traditional question answering services, users tend to contribute replies rather than questions for help in the CQA system. Inspired by the findings, we seek ways to evaluate the users＇ ability to offer prompt and reliable help, taking into account activity, authority and social reputation char- acteristics. We propose a hybrid method that is based on a Question-User network and social network using optimised PageRank algorithm. Experimental results show the efficiency of the proposed method for ranking potential answer-providers.
