公开(公告)号：US20120158791A1

公开(公告)日：2012-06-21

申请号：US12975177

申请日：2010-12-21

申请人： Gjergji Kasneci ,  David Hector Stern ,  Thore Kurt Hartwig Graepel ,  Ralf Herbrich

发明人： Gjergji Kasneci ,  David Hector Stern ,  Thore Kurt Hartwig Graepel ,  Ralf Herbrich

IPC分类号： G06F17/30

CPC分类号： G06F16/9024

摘要： Feature vector construction techniques are described. In one or more implementations, an input is received at a computing device that describes a graph query that specifies one of a plurality of entities to be used to query a knowledge base graph that represents the plurality of entities. A feature vector is constructed, by the computing device, having a number of indicator variables, each of which indicates observance of a sub-graph feature represented by a respective indicator variable in the knowledge base graph.

摘要翻译： 描述特征向量构造技术。 在一个或多个实现中，在描述指定用于查询表示多个实体的知识库的多个实体中的一个实体的图形查询的计算设备处接收输入。 由计算装置构建特征向量，其具有多个指示符变量，每个指标变量表示在知识库中由各个指示符变量表示的子图特征的遵循。

公开(公告)号：US08706653B2

公开(公告)日：2014-04-22

申请号：US12963352

申请日：2010-12-08

申请人： Gjergji Kasneci ,  Jurgen Anne Francois Marie Van Gael ,  Thore Kraepel ,  Ralf Herbrich ,  David Stern

发明人： Gjergji Kasneci ,  Jurgen Anne Francois Marie Van Gael ,  Thore Kraepel ,  Ralf Herbrich ,  David Stern

IPC分类号： G06F15/18

CPC分类号： G06N7/005

摘要： Knowledge corroboration is described. In an embodiment many judges provide answers to many questions so that at least one answer is provided to each question and at least some of the questions have answers from more than one judge. In an example a probabilistic learning system takes features describing the judges or the questions or both and uses those features to learn an expertise of each judge. For example, the probabilistic learning system has a graphical assessment component which aggregates the answers in a manner which takes into account the learnt expertise in order to determine enhanced answers. In an example the enhanced answers are used for knowledge base clean-up or web-page classification and the learnt expertise is used to select judges for future questions. In an example the probabilistic learning system has a logical component that propagates answers according to logical relations between the questions.

摘要翻译： 描述知识佐证。 在一个实施例中，许多法官为许多问题提供答案，使得至少一个答案被提供给每个问题，并且至少一些问题具有来自多于一个法官的答案。 在一个例子中，概率学习系统采用描述法官或问题或两者的特征，并使用这些特征来学习每个法官的专业知识。 例如，概率学习系统具有图形评估组件，其以考虑到所学习的专业知识的方式聚集答案，以便确定增强的答案。 在一个例子中，增强的答案用于知识库清理或网页分类，并且学习的专业知识用于为将来的问题选择法官。 在一个例子中，概率学习系统具有根据问题之间的逻辑关系传播答案的逻辑组件。

公开(公告)号：US20120150771A1

公开(公告)日：2012-06-14

申请号：US12963352

申请日：2010-12-08

申请人： Gjergji Kasneci ,  Jurgen Ann Francois Marie Van Gael ,  Thore Graepel ,  Ralf Herbrich ,  David Stern

发明人： Gjergji Kasneci ,  Jurgen Ann Francois Marie Van Gael ,  Thore Graepel ,  Ralf Herbrich ,  David Stern

IPC分类号： G06F15/18

CPC分类号： G06N7/005

摘要： Knowledge corroboration is described. In an embodiment many judges provide answers to many questions so that at least one answer is provided to each question and at least some of the questions have answers from more than one judge. In an example a probabilistic learning system takes features describing the judges or the questions or both and uses those features to learn an expertise of each judge. For example, the probabilistic learning system has a graphical assessment component which aggregates the answers in a manner which takes into account the learnt expertise in order to determine enhanced answers. In an example the enhanced answers are used for knowledge base clean-up or web-page classification and the learnt expertise is used to select judges for future questions. In an example the probabilistic learning system has a logical component that propagates answers according to logical relations between the questions.

摘要翻译： 描述知识佐证。 在一个实施例中，许多法官为许多问题提供答案，使得至少一个答案被提供给每个问题，并且至少一些问题具有来自多于一个法官的答案。 在一个例子中，概率学习系统采用描述法官或问题或两者的特征，并使用这些特征来学习每个法官的专业知识。 例如，概率学习系统具有图形评估组件，其以考虑到所学习的专业知识的方式聚集答案，以便确定增强的答案。 在一个例子中，增强的答案用于知识库清理或网页分类，并且学习的专业知识用于为将来的问题选择法官。 在一个例子中，概率学习系统具有根据问题之间的逻辑关系传播答案的逻辑组件。