公开(公告)号：US20110087655A1

公开(公告)日：2011-04-14

申请号：US12576534

申请日：2009-10-09

申请人： Ruiqiang Zhang ,  Yi Chang ,  Anlei Dong ,  Zhaohui Zheng

发明人： Ruiqiang Zhang ,  Yi Chang ,  Anlei Dong ,  Zhaohui Zheng

IPC分类号： G06F17/30

CPC分类号： G06F16/9535

摘要： In one embodiment, a method comprises accessing a search query received at a search engine; identifying a plurality of network resources for the search query; calculating a ranking score for each of the network resources; determining whether the search query is year-qualified; and if the search query is year-qualified, then adjusting the ranking scores of selected ones of the network resources based on a difference between the ranking score of an oldest one of the network resources and the ranking score of a newest one of the network resources and a confidence score representing a likelihood that the search query is year-qualified.

摘要翻译： 在一个实施例中，一种方法包括访问在搜索引擎处接收的搜索查询; 识别搜索查询的多个网络资源; 计算每个网络资源的排名得分; 确定搜索查询是否合格; 并且如果搜索查询是合格的，则基于网络资源中最老的一个网络资源的排名分数与最新的一个网络资源的排名得分之间的差异来调整所选择的网络资源的排名得分 以及表示搜索查询符合年限的可能性的置信度分数。

公开(公告)号：US20120016772A1

公开(公告)日：2012-01-19

申请号：US12838169

申请日：2010-07-16

申请人： Narayanan Sadagopan ,  Zhaohui Zheng

发明人： Narayanan Sadagopan ,  Zhaohui Zheng

IPC分类号： G06Q30/00 ,  G06F17/30

CPC分类号： G06F17/30867 ,  G06F17/30657 ,  G06F17/30684 ,  G06Q30/02 ,  G06Q30/0641

摘要： A server determines a plurality of immediate candidate items for a first web page to recommend to a user. For each particular immediate candidate item of the plurality of immediate candidate items, the server determines a separate sequence of two or more subsequent possible candidate items for subsequent web pages to recommend to the user in the event that the user selects the particular immediate candidate item. Further, the server selects a particular immediate candidate item from the plurality of immediate candidate items for the first web page to recommend to the user. The first web page that recommends the plurality of immediate candidate items is generated and sent over the Internet to the user.

摘要翻译： 服务器确定用于第一网页的多个即时候选项目以推荐给用户。 对于多个即时候选项目中的每个特定即时候选项目，服务器确定用于后续网页的两个或更多个后续可能候选项目的单独序列，以在用户选择特定直接候选项目的情况下推荐给用户。 此外，服务器从第一网页的多个直接候选项目中选择特定的即时候选项目以向用户推荐。 建立多个即时候选项目的第一网页通过因特网生成并发送给用户。

公开(公告)号：US08583502B2

公开(公告)日：2013-11-12

申请号：US12838169

申请日：2010-07-16

申请人： Narayanan Sadagopan ,  Zhaohui Zheng

发明人： Narayanan Sadagopan ,  Zhaohui Zheng

IPC分类号： G06Q30/00

CPC分类号： G06F17/30867 ,  G06F17/30657 ,  G06F17/30684 ,  G06Q30/02 ,  G06Q30/0641

摘要： A server determines a plurality of immediate candidate items for a first web page to recommend to a user. For each particular immediate candidate item of the plurality of immediate candidate items, the server determines a separate sequence of two or more subsequent possible candidate items for subsequent web pages to recommend to the user in the event that the user selects the particular immediate candidate item. Further, the server selects a particular immediate candidate item from the plurality of immediate candidate items for the first web page to recommend to the user. The first web page that recommends the plurality of immediate candidate items is generated and sent over the Internet to the user.

摘要翻译： 服务器确定用于第一网页的多个即时候选项目以推荐给用户。 对于多个即时候选项目中的每个特定即时候选项目，服务器确定用于后续网页的两个或更多个后续可能候选项目的单独序列，以在用户选择特定直接候选项目的情况下推荐给用户。 此外，服务器从第一网页的多个直接候选项目中选择特定的即时候选项目以向用户推荐。 建立多个即时候选项目的第一网页通过因特网生成并发送给用户。

公开(公告)号：US08489590B2

公开(公告)日：2013-07-16

申请号：US12966983

申请日：2010-12-13

申请人： Yi Chang ,  Zhaohui Zheng ,  Fernando David Diaz ,  Jing Bai

发明人： Yi Chang ,  Zhaohui Zheng ,  Fernando David Diaz ,  Jing Bai

IPC分类号： G06F7/00 ,  G06F17/30

CPC分类号： G06F17/30864

摘要： Embodiments are directed towards generating market-specific ranking models by leveraging target market specific pairwise preference data. The pairwise preference data includes market-specific training examples, while a ranking model from another market captures the common characteristics of the resulting ranking model. In one embodiment, the ranking model is trained by applying a Tree Based Ranking Function Adaptation (TRADA) algorithm to multi-grade labeled training data, such as editorially generated training data. Then, contradictions between the TRADA generated ranking model and target-market specific pairwise preference data are identified. For each identified contradiction, new training data is generated to correct the contradiction. Then, in one embodiment, an algorithm such as TRADA is applied to the existing ranking model and the new training data to generate a new ranking model.

摘要翻译： 实施例旨在通过利用目标市场特定的成对偏好数据来产生市场特定的排名模型。 成对偏好数据包括市场特定的培训示例，而来自另一个市场的排名模型捕获了所得到的排名模型的共同特征。 在一个实施例中，通过将基于树的排序函数适应（TRADA）算法应用于诸如编辑生成的训练数据的多等级标记的训练数据来训练排名模型。 然后，确定了TRADA产生的排名模型和目标市场特定成对偏好数据之间的矛盾。 对于每个确定的矛盾，产生新的训练数据以纠正矛盾。 然后，在一个实施例中，诸如TRADA的算法被应用于现有的排名模型和新的训练数据以生成新的排名模型。

公开(公告)号：US20130132401A1

公开(公告)日：2013-05-23

申请号：US13298932

申请日：2011-11-17

申请人： Taesup Moon ,  Zhaohui Zheng ,  Yi Chang ,  Pranam Kolari ,  Xuanhui Wang ,  Yuanhua Lv

发明人： Taesup Moon ,  Zhaohui Zheng ,  Yi Chang ,  Pranam Kolari ,  Xuanhui Wang ,  Yuanhua Lv

IPC分类号： G06F17/30

CPC分类号： G06F17/30864 ,  G06F17/30967 ,  G06F17/30994

摘要： Methods, systems, and computer programs are presented for providing internet content, such as related news articles. One method includes an operation for defining a plurality of candidates based on a seed. For each candidate, scores are calculated for relevance, novelty, connection clarity, and transition smoothness. The score for connection clarity is based on a relevance score of the intersection between the words in the seed and the words in each of the candidates. Further, the score for transition smoothness measures the interest in reading each candidate when transitioning from the seed to the candidate. For each candidate, a relatedness score is calculated based on the calculated scores for relevance, novelty, connection clarity, and transition smoothness. In addition, at least one of the candidates is selected based on their relatedness scores for presentation to the user.

摘要翻译： 提供方法，系统和计算机程序，用于提供互联网内容，如相关的新闻文章。 一种方法包括基于种子定义多个候选的操作。 对于每个候选人，计算相关性，新颖性，连接清晰度和过渡平滑度的分数。 连接清晰度的分数基于种子中的单词和每个候选词中的单词之间的交集的相关性分数。 此外，过渡平滑度的得分衡量了从种子转移到候选人时阅读每个候选人的兴趣。 对于每个候选人，根据相关性，新颖性，连接清晰度和过渡平滑度的计算分数计算相关性分数。 此外，基于用于呈现给用户的相关性分数来选择至少一个候选者。

公开(公告)号：US08713028B2

公开(公告)日：2014-04-29

申请号：US13298932

申请日：2011-11-17

申请人： Taesup Moon ,  Zhaohui Zheng ,  Yi Chang ,  Pranam Kolari ,  Xuanhui Wang ,  Yuanhua Lv

发明人： Taesup Moon ,  Zhaohui Zheng ,  Yi Chang ,  Pranam Kolari ,  Xuanhui Wang ,  Yuanhua Lv

IPC分类号： G06F17/30

CPC分类号： G06F17/30864 ,  G06F17/30967 ,  G06F17/30994

摘要： Methods, systems, and computer programs are presented for providing internet content, such as related news articles. One method includes an operation for defining a plurality of candidates based on a seed. For each candidate, scores are calculated for relevance, novelty, connection clarity, and transition smoothness. The score for connection clarity is based on a relevance score of the intersection between the words in the seed and the words in each of the candidates. Further, the score for transition smoothness measures the interest in reading each candidate when transitioning from the seed to the candidate. For each candidate, a relatedness score is calculated based on the calculated scores for relevance, novelty, connection clarity, and transition smoothness. In addition, at least one of the candidates is selected based on their relatedness scores for presentation to the user.

摘要翻译： 提供方法，系统和计算机程序，用于提供互联网内容，如相关的新闻文章。 一种方法包括基于种子定义多个候选的操作。 对于每个候选人，计算相关性，新颖性，连接清晰度和过渡平滑度的分数。 连接清晰度的分数基于种子中的单词和每个候选词中的单词之间的交集的相关性分数。 此外，过渡平滑度的得分衡量了从种子转移到候选人时阅读每个候选人的兴趣。 对于每个候选人，根据相关性，新颖性，连接清晰度和过渡平滑度的计算分数计算相关性分数。 此外，基于用于呈现给用户的相关性分数来选择至少一个候选者。

公开(公告)号：US20120150855A1

公开(公告)日：2012-06-14

申请号：US12966983

申请日：2010-12-13

申请人： Yi Chang ,  Zhaohui Zheng ,  Fernando David Diaz ,  Jing Bai

发明人： Yi Chang ,  Zhaohui Zheng ,  Fernando David Diaz ,  Jing Bai

IPC分类号： G06F17/30

CPC分类号： G06F17/30864

摘要： Embodiments are directed towards generating market-specific ranking models by leveraging target market specific pairwise preference data. The pairwise preference data includes market-specific training examples, while a ranking model from another market captures the common characteristics of the resulting ranking model. In one embodiment, the ranking model is trained by applying a Tree Based Ranking Function Adaptation (TRADA) algorithm to multi-grade labeled training data, such as editorially generated training data. Then, contradictions between the TRADA generated ranking model and target-market specific pairwise preference data are identified. For each identified contradiction, new training data is generated to correct the contradiction. Then, in one embodiment, an algorithm such as TRADA is applied to the existing ranking model and the new training data to generate a new ranking model.

摘要翻译： 实施例旨在通过利用目标市场特定的成对偏好数据来产生市场特定的排名模型。 成对偏好数据包括市场特定的培训示例，而来自另一个市场的排名模型捕获了所得到的排名模型的共同特征。 在一个实施例中，通过将基于树的排序函数适应（TRADA）算法应用于诸如编辑生成的训练数据的多等级标记的训练数据来训练排名模型。 然后，确定了TRADA产生的排名模型和目标市场特定成对偏好数据之间的矛盾。 对于每个确定的矛盾，产生新的训练数据以纠正矛盾。 然后，在一个实施例中，诸如TRADA的算法被应用于现有的排名模型和新的训练数据以生成新的排名模型。

公开(公告)号：US09443008B2

公开(公告)日：2016-09-13

申请号：US12835954

申请日：2010-07-14

申请人： Srinivas Vadrevu ,  Yi Chang ,  Zhaohui Zheng ,  Bo Long

发明人： Srinivas Vadrevu ,  Yi Chang ,  Zhaohui Zheng ,  Bo Long

IPC分类号： G06F17/30

CPC分类号： G06F17/30705 ,  G06F17/30011 ,  G06F17/30675 ,  G06F17/30696

摘要： One particular embodiment clusters a plurality of documents using one or more clustering algorithms to obtain one or more first sets of clusters, wherein: each first set of clusters results from clustering the documents using one of the clustering algorithms; and with respect to each first set of clusters, each of the documents belongs to one of the clusters from the first set of clusters; accesses a search query; identifies a search result in response to the search query, wherein the search result comprises two or more of the documents; and clusters the search result to obtain a second set of clusters, wherein each document of the search result belongs to one of the clusters from the second set of clusters.

摘要翻译： 一个特定实施例使用一个或多个聚类算法来聚集多个文档以获得一个或多个第一组聚类，其中：每个第一组聚类是使用聚类算法之一聚类文档而得到的; 并且对于每个第一组集合，每个文档属于来自第一组集合的集群之一; 访问搜索查询; 识别响应于搜索查询的搜索结果，其中搜索结果包括两个或更多个文档; 并且聚集搜索结果以获得第二组聚类，其中搜索结果的每个文档属于来自第二组聚类的聚类中的一个。

公开(公告)号：US20120016877A1

公开(公告)日：2012-01-19

申请号：US12835954

申请日：2010-07-14

申请人： Srinivas Vadrevu ,  Yi Chang ,  Zhaohui Zheng ,  Bo Long

发明人： Srinivas Vadrevu ,  Yi Chang ,  Zhaohui Zheng ,  Bo Long

IPC分类号： G06F17/30

CPC分类号： G06F17/30705 ,  G06F17/30011 ,  G06F17/30675 ,  G06F17/30696

摘要： One particular embodiment clusters a plurality of documents using one or more clustering algorithms to obtain one or more first sets of clusters, wherein: each first set of clusters results from clustering the documents using one of the clustering algorithms; and with respect to each first set of clusters, each of the documents belongs to one of the clusters from the first set of clusters; accesses a search query; identifies a search result in response to the search query, wherein the search result comprises two or more of the documents; and clusters the search result to obtain a second set of clusters, wherein each document of the search result belongs to one of the clusters from the second set of clusters.

摘要翻译： 一个特定实施例使用一个或多个聚类算法来聚集多个文档以获得一个或多个第一组聚类，其中：每个第一组聚类是使用聚类算法之一聚类文档而得到的; 并且对于每个第一组集合，每个文档属于来自第一组集合的集群之一; 访问搜索查询; 识别响应于搜索查询的搜索结果，其中所述搜索结果包括所述文档中的两个或更多个; 并且聚集搜索结果以获得第二组聚类，其中搜索结果的每个文档属于来自第二组聚类的聚类中的一个。

公开(公告)号：US20150112918A1

公开(公告)日：2015-04-23

申请号：US14385274

申请日：2012-03-17

申请人： Zhaohui Zheng ,  Xin Li ,  Rongqing Lu ,  Shuanghong Yang

发明人： Zhaohui Zheng ,  Xin Li ,  Rongqing Lu ,  Shuanghong Yang

IPC分类号： G06F17/30 ,  G06N5/04

摘要： Method, system, and programs for recommending content to a user. First information related to one or more previous users is first obtained. A model that maps from users to topics of interest is then established based on the first information related to the one or more previous users. Second information related to the current user is also obtained. One or more topics of interest are identified for the current user based on the model. Content is recommended to the current user in accordance with the one or more topics of interest for the current user. Eventually, an updated model is generated by integrating information associated with the current user with the model established based on the first information related to the one or more previous users. The information associated with the current user includes the second information related to the current user.

摘要翻译： 用于向用户推荐内容的方法，系统和程序。 首先获得与一个或多个先前用户相关的第一信息。 然后基于与一个或多个先前用户相关的第一信息建立从用户映射到感兴趣主题的模型。 还获得了与当前用户相关的第二信息。 基于该模型为当前用户识别感兴趣的一个或多个主题。 根据当前用户感兴趣的一个或多个主题向当前用户推荐内容。 最终，通过将与当前用户相关联的信息与基于与一个或多个先前用户相关的第一信息建立的模型进行集成来生成更新的模型。 与当前用户相关联的信息包括与当前用户相关的第二信息。