公开(公告)号：US20110131168A1

公开(公告)日：2011-06-02

申请号：US12936811

申请日：2009-04-02

申请人： Yusuke Fukazawa ,  Mirai Hara ,  Hidetoshi Ueno ,  Masashi Onogi ,  Takefumi Naganuma ,  Midori Onogi ,  Shoji Kurakake

发明人： Yusuke Fukazawa ,  Mirai Hara ,  Hidetoshi Ueno ,  Masashi Onogi ,  Takefumi Naganuma ,  Midori Onogi ,  Shoji Kurakake

IPC分类号： G06N5/02

CPC分类号： G06F17/30867 ,  G06F17/30029

摘要： A content evaluation apparatus and a content evaluation method that can distribute contents that a user potentially needs without any omissions. A history class separation unit generates a separation plane for separating in a separation plane a characteristic vector of a selected content and characteristic vectors of non-selected contents stored in a browsing history table. A user characteristic vector calculation unit generates a user characteristic vector based on an orthogonal vector perpendicular to the separation plane thus generated and stores the user characteristic vector in a user characteristic vector management table. Subsequently, when a recommendation request receiving unit receives a recommendation request, a content evaluation unit evaluates the contents based on the stored user characteristic vector.

摘要翻译： 内容评价装置和内容评价方法，其能够分发用户可能需要的内容而没有任何遗漏。 历史类分离单元生成用于在分离平面中分离所选内容的特征向量和存储在浏览历史表中的未选择内容的特征向量的分离平面。 用户特征向量计算单元基于垂直于所生成的分离平面的正交矢量生成用户特征向量，并将用户特征向量存储在用户特征向量管理表中。 随后，当推荐请求接收单元接收推荐请求时，内容评估单元基于所存储的用户特征向量来评估内容。

公开(公告)号：US20110093476A1

公开(公告)日：2011-04-21

申请号：US12936758

申请日：2009-04-02

申请人： Yusuke Fukazawa ,  Mirai Hara ,  Hidetoshi Ueno ,  Masashi Onogi ,  Takefumi Naganuma ,  Midori Onogi ,  Shoji Kurakake

发明人： Yusuke Fukazawa ,  Mirai Hara ,  Hidetoshi Ueno ,  Masashi Onogi ,  Takefumi Naganuma ,  Midori Onogi ,  Shoji Kurakake

IPC分类号： G06F17/30

CPC分类号： G06F17/30867

摘要： A recommendation information generation apparatus and a recommendation information generation method that can select a similar user appropriately even if the amount of history information is small. In an information distribution server, a user characteristic vector calculation unit calculates a user characteristic vector of each of users, and a similar user calculation unit calculates the degree of similarity between the users based on the calculated user characteristic vector of each of the users. The similar user calculation unit then selects a similar user who is similar to a first user based on the calculated degree of similarity. A relevance evaluation unit generates recommendation information for the first user based on the characteristic vector of the selected similar user.

摘要翻译： 即使历史信息量少的情况，也能够适当地选择类似的用户的推荐信息生成装置和推荐信息生成方法。 在信息分发服务器中，用户特征向量计算单元计算每个用户的用户特征向量，并且类似的用户计算单元基于所计算的每个用户的用户特征向量来计算用户之间的相似度。 类似用户计算单元然后基于所计算的相似程度来选择类似于第一用户的类似用户。 相关性评估单元基于所选择的类似用户的特征向量生成第一用户的推荐信息。

公开(公告)号：US08886583B2

公开(公告)日：2014-11-11

申请号：US12936811

申请日：2009-04-02

申请人： Yusuke Fukazawa ,  Mirai Hara ,  Hidetoshi Ueno ,  Masashi Onogi ,  Takefumi Naganuma ,  Midori Onogi ,  Shoji Kurakake

发明人： Yusuke Fukazawa ,  Mirai Hara ,  Hidetoshi Ueno ,  Masashi Onogi ,  Takefumi Naganuma ,  Midori Onogi ,  Shoji Kurakake

IPC分类号： G06F17/00 ,  G06N5/02 ,  G06F17/30

CPC分类号： G06F17/30867 ,  G06F17/30029

摘要： A content evaluation apparatus and a content evaluation method that can distribute contents that a user potentially needs without any omissions. A history class separation unit generates a separation plane for separating in a separation plane a characteristic vector of a selected content and characteristic vectors of non-selected contents stored in a browsing history table. A user characteristic vector calculation unit generates a user characteristic vector based on an orthogonal vector perpendicular to the separation plane thus generated and stores the user characteristic vector in a user characteristic vector management table. Subsequently, when a recommendation request receiving unit receives a recommendation request, a content evaluation unit evaluates the contents based on the stored user characteristic vector.

摘要翻译： 内容评价装置和内容评价方法，其能够分发用户可能需要的内容而没有任何遗漏。 历史类分离单元生成用于在分离平面中分离所选内容的特征向量和存储在浏览历史表中的未选择内容的特征向量的分离平面。 用户特征向量计算单元基于垂直于所生成的分离平面的正交矢量生成用户特征向量，并将用户特征向量存储在用户特征向量管理表中。 随后，当推荐请求接收单元接收推荐请求时，内容评估单元基于所存储的用户特征向量来评估内容。

公开(公告)号：US08032526B2

公开(公告)日：2011-10-04

申请号：US12936758

申请日：2009-04-02

申请人： Yusuke Fukazawa ,  Mirai Hara ,  Hidetoshi Ueno ,  Masashi Onogi ,  Takefumi Naganuma ,  Midori Onogi ,  Shoji Kurakake

发明人： Yusuke Fukazawa ,  Mirai Hara ,  Hidetoshi Ueno ,  Masashi Onogi ,  Takefumi Naganuma ,  Midori Onogi ,  Shoji Kurakake

IPC分类号： G06F17/30

CPC分类号： G06F17/30867

摘要： A recommendation information generation apparatus and a recommendation information generation method that can select a similar user appropriately even if the amount of history information is small. In an information distribution server, a user characteristic vector calculation unit calculates a user characteristic vector of each of users, and a similar user calculation unit calculates the degree of similarity between the users based on the calculated user characteristic vector of each of the users. The similar user calculation unit then selects a similar user who is similar to a first user based on the calculated degree of similarity. A relevance evaluation unit generates recommendation information for the first user based on the characteristic vector of the selected similar user.

摘要翻译： 即使历史信息量少的情况，也能够适当地选择类似的用户的推荐信息生成装置和推荐信息生成方法。 在信息分发服务器中，用户特征向量计算单元计算每个用户的用户特征向量，并且类似的用户计算单元基于所计算的每个用户的用户特征向量来计算用户之间的相似度。 类似用户计算单元然后基于所计算的相似程度来选择类似于第一用户的类似用户。 相关性评估单元基于所选择的类似用户的特征向量生成第一用户的推荐信息。