公开(公告)号：US20090006326A1

公开(公告)日：2009-01-01

申请号：US11770307

申请日：2007-06-28

申请人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

发明人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

IPC分类号： G06F17/30

CPC分类号： G06Q30/02

摘要： Representing queries and determining similarity of queries based on an autoregressive integrated moving average (“ARIMA”) model is provided. A query analysis system represents each query by its ARIMA coefficients. The query analysis system may estimate the frequency information for a desired past or future interval based on frequency information for some initial intervals. The query analysis system may also determine the similarity of a pair of queries based on the similarity of their ARIMA coefficients. The query analysis system may use various metrics, such as a correlation metric, to determine the similarity of the ARIMA coefficients.

摘要翻译： 提供了基于自回归综合移动平均（“ARIMA”）模型的查询和确定查询的相似性。 查询分析系统通过其ARIMA系数表示每个查询。 查询分析系统可以基于一些初始间隔的频率信息来估计期望的过去或将来间隔的频率信息。 查询分析系统还可以基于它们的ARIMA系数的相似度来确定一对查询的相似性。 查询分析系统可以使用诸如相关度量的各种度量来确定ARIMA系数的相似性。

公开(公告)号：US20090006313A1

公开(公告)日：2009-01-01

申请号：US11770462

申请日：2007-06-28

申请人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

发明人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

IPC分类号： G06F17/40

CPC分类号： G06Q30/02

摘要： Techniques for analyzing and modeling the frequency of queries are provided by a query analysis system. A query analysis system analyzes frequencies of a query over time to determine whether the query is time-dependent or time-independent. The query analysis system forecasts the frequency of time-dependent queries based on their periodicities. The query analysis system forecasts the frequency of time-independent queries based on causal relationships with other queries. To forecast the frequency of time-independent queries, the query analysis system analyzes the frequency of a query over time to identify significant increases in the frequency, which are referred to as “query events” or “events.” The query analysis system forecasts frequencies of time-independent queries based on queries with events that tend to causally precede events of the query to be forecasted.

摘要翻译： 用于分析和建模查询频率的技术由查询分析系统提供。 查询分析系统分析查询的频率，以确定查询是时间依赖还是时间无关。 查询分析系统根据其周期性预测与时间相关的查询的频率。 查询分析系统根据与其他查询的因果关系预测与时间无关的查询的频率。 为了预测与时间无关的查询的频率，查询分析系统会随着时间的推移分析查询的频率，以确定频率的显着增加，这被称为“查询事件”或“事件”。 查询分析系统基于具有事件倾向于在要预测的查询的事件之前的查询来预测与时间无关的查询的频率。

公开(公告)号：US20090006312A1

公开(公告)日：2009-01-01

申请号：US11770358

申请日：2007-06-28

申请人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

发明人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

IPC分类号： G06F7/00

CPC分类号： G06F17/30864 ,  G06Q30/02

摘要： Techniques for analyzing and modeling the frequency of queries are provided by a query analysis system. A query analysis system analyzes frequencies of a query over time to determine whether the query is time-dependent or time-independent. The query analysis system forecasts the frequency of time-dependent queries based on their periodicities. The query analysis system forecasts the frequency of time-independent queries based on causal relationships with other queries. To forecast the frequency of time-independent queries, the query analysis system analyzes the frequency of a query over time to identify significant increases in the frequency, which are referred to as “query events” or “events.” The query analysis system forecasts frequencies of time-independent queries based on queries with events that tend to causally precede events of the query to be forecasted.

摘要翻译： 用于分析和建模查询频率的技术由查询分析系统提供。 查询分析系统分析查询的频率，以确定查询是时间依赖还是时间无关。 查询分析系统根据其周期性预测与时间相关的查询的频率。 查询分析系统根据与其他查询的因果关系预测与时间无关的查询的频率。 为了预测与时间无关的查询的频率，查询分析系统会随着时间的推移分析查询的频率，以确定频率的显着增加，这被称为“查询事件”或“事件”。 查询分析系统基于具有事件倾向于在要预测的查询的事件之前的查询来预测与时间无关的查询的频率。

公开(公告)号：US09020947B2

公开(公告)日：2015-04-28

申请号：US13307836

申请日：2011-11-30

申请人： Jun Yan ,  Lei Ji ,  Ning Liu ,  Zheng Chen

发明人： Jun Yan ,  Lei Ji ,  Ning Liu ,  Zheng Chen

IPC分类号： G06F7/00 ,  G06F17/30

CPC分类号： G06F17/30702 ,  G06F17/30867

摘要： Techniques are described for generating structured information from semi-structured web pages, and retrieving the structured knowledge in response to a user query that indicates a query intent. The structured information is automatically extracted offline from semi-structured web pages, through the use of an auto wrapper solution that is noise tolerant, scalable, and automatic. The structured information is stored in a knowledge base, and provided in response to a user search query that indicates a query intent. Extraction of structured information may also include clustering of pages based on their measured similarities. The clusters may be determined based on similar elements in the tag path text data of the pages. A minimum size threshold may be applied to the clusters.

摘要翻译： 描述了用于从半结构化网页生成结构化信息的技术，以及响应于指示查询意图的用户查询来检索结构化知识。 结构化信息通过使用具有噪声容限，可扩展和自动的自动包装解决方案，从半结构化网页离线自动提取。 结构化信息存储在知识库中，并响应于指示查询意图的用户搜索查询而提供。 结构化信息的提取还可以包括基于其测量的相似性来聚合页面。 可以基于页面的标签路径文本数据中的类似元素来确定簇。 可以将最小大小阈值应用于群集。

公开(公告)号：US20140052751A1

公开(公告)日：2014-02-20

申请号：US13586711

申请日：2012-08-15

申请人： Jianwen Zhang ,  Zhimin Zhang ,  Jian-Tao Sun ,  Jun Yan ,  Ning Liu ,  Lei Ji ,  Weizhu Chen ,  Zheng Chen

发明人： Jianwen Zhang ,  Zhimin Zhang ,  Jian-Tao Sun ,  Jun Yan ,  Ning Liu ,  Lei Ji ,  Weizhu Chen ,  Zheng Chen

IPC分类号： G06F17/30

CPC分类号： G06F17/30032 ,  G06F17/30905

摘要： A smart user-centric information aggregation system allows a user to define a region of content displayed in a display of a device and performs information aggregation on behalf of the user. The smart user-centric information aggregation system searches, aggregates and groups information related to content included in the region of content for the user while the user can continue to perform his/her original course of actions without interruption. After finding information related to the desired content, the smart user-centric information aggregation system may notify the user and present the found information to the user upon receiving confirmation from the user. The smart user-centric information aggregation system may continue to find new related information and update the presentation with the newly found information periodically, in some instances without user intervention or input.

摘要翻译： 以智能用户为中心的信息聚合系统允许用户定义显示在设备显示器中的内容区域，并代表用户执行信息聚合。 智能用户为中心的信息聚合系统在用户可以继续执行他/她的原始行为过程而不间断地搜索，聚合和分组与用户内容区域中包含的内容相关的信息。 在找到与期望内容相关的信息之后，智能用户为中心的信息聚合系统可以在接收到来自用户的确认时通知用户并向用户呈现找到的信息。 以智能用户为中心的信息聚合系统可以继续寻找新的相关信息，并且在某些情况下，不需要用户干预或输入，定期更新新发现的信息。

公开(公告)号：US08533188B2

公开(公告)日：2013-09-10

申请号：US13235140

申请日：2011-09-16

申请人： Jun Yan ,  Ning Liu ,  Lei Ji ,  Steven J. Hanks ,  Qing Xu ,  Zheng Chen

发明人： Jun Yan ,  Ning Liu ,  Lei Ji ,  Steven J. Hanks ,  Qing Xu ,  Zheng Chen

IPC分类号： G06F17/30

CPC分类号： G06F17/30321 ,  G06F17/30867

摘要： Embodiments facilitate greater flexibility in definition of user segments for targeted advertising, by employing indexed semantic user profiles. Semantic user profiles are built through extraction of online user behavior data such as user search queries and page views, and include user interest information that is inferred based on user behavior. Semantic user profiles are then indexed to facilitate search for a set of users that fit specified semantic search terms. Search results for semantic profiles are ranked according to a ranking model developed through machine learning. In some embodiments, building and indexing of semantic profiles and learning of the ranking model is performed offline to facilitate more efficient online processing of queries.

摘要翻译： 实施例通过采用索引语义用户简档来促进用于定向广告的用户段的定义的更大的灵活性。 通过提取在线用户行为数据（如用户搜索查询和页面浏览）构建语义用户配置文件，并包括基于用户行为推断的用户兴趣信息。 然后索引语义用户简档，以便于搜索适合指定语义搜索术语的一组用户。 根据通过机器学习开发的排名模型对语义轮廓的搜索结果进行排名。 在一些实施例中，离线地执行语义概况的构建和索引以及排名模型的学习，以便更有效地在线处理查询。

公开(公告)号：US20120278162A1

公开(公告)日：2012-11-01

申请号：US13097081

申请日：2011-04-29

申请人： Jiantao Sun ,  Jun Yan ,  Lei Ji ,  Ning Liu ,  Peng Bai ,  Xuedong Huang ,  Xiaochuan Ni ,  Zhimin Zhang ,  Zheng Chen

发明人： Jiantao Sun ,  Jun Yan ,  Lei Ji ,  Ning Liu ,  Peng Bai ,  Xuedong Huang ,  Xiaochuan Ni ,  Zhimin Zhang ,  Zheng Chen

IPC分类号： G06Q30/00 ,  G06F17/30 ,  G06F15/16

CPC分类号： G06Q30/0261

摘要： Various technologies pertaining to provision of graphical data to a client computing device responsive to receipt of a positional selection on a web page by a user of a client computing device are described herein. A computer-executable application executing on the client computing device detects that the user has selected a certain position on the web page, wherein this application is not called by code of the web page. The position is transmitted to an ad server, which conducts an auction for display space on the client computing device based at least in part upon the detection of the certain position.

摘要翻译： 这里描述了有关根据客户端计算设备的用户接收到网页上的位置选择而向客户计算设备提供图形数据的各种技术。 在客户端计算设备上执行的计算机可执行应用程序检测到用户已经选择了网页上的某个位置，其中该应用不被网页的代码调用。 该位置被传送到广告服务器，该广告服务器至少部分地基于对某个位置的检测来对客户端计算设备上的显示空间进行拍卖。

公开(公告)号：US20120265760A1

公开(公告)日：2012-10-18

申请号：US13089103

申请日：2011-04-18

申请人： Jun Yan ,  Ning Liu ,  Lei Ji ,  Zheng Chen

发明人： Jun Yan ,  Ning Liu ,  Lei Ji ,  Zheng Chen

IPC分类号： G06F17/30

CPC分类号： G06F17/30864

摘要： A classification process may reduce the computational resources and time required to collect and classify training data utilized to enable a user to effectively access online information. According to some implementations, training data is established by defining one or more seed queries and query patterns. A bi-partite graph may be constructed using the seed query and query pattern information. A traversal of the bi-partite graph can be performed to expand the training data to encompass sufficient data to perform classification of the present search task.

摘要翻译： 分类过程可以减少收集和分类用于使用户有效访问在线信息的训练数据所需的计算资源和时间。 根据一些实施方式，通过定义一个或多个种子查询和查询模式来建立训练数据。 可以使用种子查询和查询模式信息来构建双分图。 可以执行双分图的遍历以扩展训练数据以包括足够的数据来执行本次搜索任务的分类。

公开(公告)号：US08090709B2

公开(公告)日：2012-01-03

申请号：US11770307

申请日：2007-06-28

申请人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

发明人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

IPC分类号： G06F17/30

CPC分类号： G06Q30/02

摘要： Representing queries and determining similarity of queries based on an autoregressive integrated moving average (“ARIMA”) model is provided. A query analysis system represents each query by its ARIMA coefficients. The query analysis system may estimate the frequency information for a desired past or future interval based on frequency information for some initial intervals. The query analysis system may also determine the similarity of a pair of queries based on the similarity of their ARIMA coefficients. The query analysis system may use various metrics, such as a correlation metric, to determine the similarity of the ARIMA coefficients.

摘要翻译： 提供了基于自回归综合移动平均（“ARIMA”）模型的查询和确定查询的相似性。 查询分析系统通过其ARIMA系数表示每个查询。 查询分析系统可以基于一些初始间隔的频率信息来估计期望的过去或将来间隔的频率信息。 查询分析系统还可以基于它们的ARIMA系数的相似度来确定一对查询的相似性。 查询分析系统可以使用诸如相关度量的各种度量来确定ARIMA系数的相似性。

公开(公告)号：US20110302155A1

公开(公告)日：2011-12-08

申请号：US12793047

申请日：2010-06-03

申请人： Jun Yan ,  Ning Liu ,  Lei Ji ,  Zheng Chen ,  Jiulong Wang ,  Xiao Liang

发明人： Jun Yan ,  Ning Liu ,  Lei Ji ,  Zheng Chen ,  Jiulong Wang ,  Xiao Liang

IPC分类号： G06F17/30

CPC分类号： G06F17/30867

摘要： The related links recommendation technique described herein employs combined collaborative filtering to recommend related web pages to users. The technique creates multiple collaborative filters which are combined in order to create a combined collaborative filter to recommend web pages similar to a given web page to a user. One query-based collaborative filter is created by using query search clicks (e.g., user input device selection actions on search results returned in response to a search query). Another user-behavior-based collaborative filter is created by using query search clicks and user clicks while browsing websites (e.g., user input device selection actions while a user is browsing websites). Lastly, another content-based collaborative filter based on similar content of web pages is created by finding web pages with similar content.

摘要翻译： 本文描述的相关链接推荐技术采用组合协同过滤来向用户推荐相关网页。 该技术创建了多个协作过滤器，这些过滤器被组合以便创建组合的协同过滤器以向用户推荐类似于给定网页的网页。 通过使用查询搜索点击创建一个基于查询的协作过滤器（例如，响应于搜索查询返回的搜索结果上的用户输入设备选择动作）。 通过在浏览网站时使用查询搜索点击和用户点击创建另一个基于用户行为的协作过滤器（例如，用户浏览网站时的用户输入设备选择动作）。 最后，通过查找具有相似内容的网页来创建基于类似内容的网页的另一基于内容的协作过滤器。