公开(公告)号：US20130097178A1

公开(公告)日：2013-04-18

申请号：US13274796

申请日：2011-10-17

申请人： Young-In Song ,  Liu Jing ,  Chin-Yew Lin ,  Tetsuya Sakai

发明人： Young-In Song ,  Liu Jing ,  Chin-Yew Lin ,  Tetsuya Sakai

IPC分类号： G06F17/30 ,  G06F15/18

CPC分类号： G09B7/02 ,  G06Q50/10 ,  G06Q50/20

摘要： Techniques for unsupervised management of a question and answer (QA) forum include labeling of answers for quality purposes, and identification of experts. In a QA thread, a ranking of answers may include an initial labeling of the longest answer in each thread as the best answer. Such a labeling provides an initial point of reference. Then, in an iterative manner answerers are ranked using the labeling. The ranking of answerers allows selection of experts and poor or inexpert answerers. A label update is performed using the experts (and perhaps inexpert answerers) as input. The label update may be used to train a model, which may describe quality of answers in one or more QA threads and an indication of expert and inexpert answerers. The iterative process may be ended upon convergence or upon a maximum number of iterations.

摘要翻译： 用于无人管理问答（QA）论坛的技术包括为质量目的标识答案，并确定专家。 在QA线程中，答案的排名可能包括每个线程中最长答案的初始标签作为最佳答案。 这样的标签提供了初步的参考点。 然后，以迭代的方式，使用标签对答复者进行排名。 回答者的排名允许选择专家和穷人或无经验的回答者。 使用专家（或许不太实际的回答者）作为输入进行标签更新。 标签更新可以用于训练模型，其可以描述一个或多个QA线程中的答案的质量以及专家和不熟练的答复者的指示。 迭代过程可以在收敛或最大迭代次数时结束。

公开(公告)号：US08473499B2

公开(公告)日：2013-06-25

申请号：US13274796

申请日：2011-10-17

申请人： Young-In Song ,  Liu Jing ,  Chin-Yew Lin ,  Tetsuya Sakai

发明人： Young-In Song ,  Liu Jing ,  Chin-Yew Lin ,  Tetsuya Sakai

IPC分类号： G06F15/18 ,  G06F17/30 ,  G06E1/00 ,  G06N5/04

CPC分类号： G09B7/02 ,  G06Q50/10 ,  G06Q50/20

摘要： Techniques for unsupervised management of a question and answer (QA) forum include labeling of answers for quality purposes, and identification of experts. In a QA thread, a ranking of answers may include an initial labeling of the longest answer in each thread as the best answer. Such a labeling provides an initial point of reference. Then, in an iterative manner answerers are ranked using the labeling. The ranking of answerers allows selection of experts and poor or inexpert answerers. A label update is performed using the experts (and perhaps inexpert answerers) as input. The label update may be used to train a model, which may describe quality of answers in one or more QA threads and an indication of expert and inexpert answerers. The iterative process may be ended upon convergence or upon a maximum number of iterations.

摘要翻译： 用于无人管理问答（QA）论坛的技术包括为质量目的标识答案，并确定专家。 在QA线程中，答案的排名可能包括每个线程中最长答案的初始标签作为最佳答案。 这样的标签提供了初步的参考点。 然后，以迭代的方式，使用标签对答复者进行排名。 回答者的排名允许选择专家和穷人或无经验的回答者。 使用专家（或许不太实际的回答者）作为输入进行标签更新。 标签更新可以用于训练模型，其可以描述一个或多个QA线程中的答案的质量以及专家和不熟练的答复者的指示。 迭代过程可以在收敛或最大迭代次数时结束。

公开(公告)号：US20130262453A1

公开(公告)日：2013-10-03

申请号：US13430928

申请日：2012-03-27

申请人： Chin-Yew Lin ,  Young-In Song ,  Jing Liu

发明人： Chin-Yew Lin ,  Young-In Song ,  Jing Liu

IPC分类号： G06F17/30

CPC分类号： G06Q50/01

摘要： The subject disclosure is directed towards ranking participants in an online platform according to expertise. A competition-based metric is applied to question and answer threads in order to model each thread as a set of comparisons between various groups of the participants. After aggregating comparison results for the question and answer treads, one or more relative expertise scores may be estimated for each participant. Each relative expertise score may correspond to a specific category of questions.

摘要翻译： 主题披露旨在根据专业知识在线平台上的参与者排名。 基于竞争的度量被应用于问答线程，以便将每个线程建模为参与者的各组之间的一组比较。 在对问题和答案的比较结果进行总结之后，可以为每个参与者估计一个或多个相对专业知识得分。 每个相关专业评分可能对应于特定类别的问题。

公开(公告)号：US20100235343A1

公开(公告)日：2010-09-16

申请号：US12569553

申请日：2009-09-29

申请人： Yunbo Cao ,  Chin-Yew Lin ,  Young-In Song

发明人： Yunbo Cao ,  Chin-Yew Lin ,  Young-In Song

IPC分类号： G06F17/30

CPC分类号： G06Q30/02 ,  G06F16/951

摘要： Exemplary methods, computer-readable media, and systems are presented for learning to recommend questions and other user-generated submissions to community sites based on user ratings. The size of available training data is enlarged by taking into consideration questions without user ratings, which in turn benefits the learned model. Question or other user-generated submissions are obtained by crawling Internet-accessible Web sites including community sites. Questions and other submissions, even when not tagged, voted or indicated as “popular” or “interesting” by users are quantitatively indentified as “interesting.”

摘要翻译： 呈现示例性方法，计算机可读介质和系统，用于基于用户评级学习向社区网站推荐问题和其他用户生成的提交。 通过考虑没有用户评级的问题来扩大可用的培训数据的大小，这又有利于学习模式。 通过抓取可上网的网站（包括社区网站）获取问题或其他用户生成的提交内容。 问题和其他提交内容，即使没有标记，用户投票或表示为“受欢迎”或“有趣”，也被定义为“有趣”。