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91. 发明授权

US08543580B2 Mining translations of web queries from web click-through data 有权
标题翻译：从网络点击数据挖掘网络查询的翻译
公开(公告)号：US08543580B2
公开(公告)日：2013-09-24
申请号：US12342098
申请日：2008-12-23
申请人： Weizhu Chen , Zheng Chen
发明人： Weizhu Chen , Zheng Chen
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/30864 , G06F2216/03
摘要： Methods and technologies providing translations of web queries based on an analysis of user behavior in click-through data. These methods and technologies generates large-scale and timely query translation pairs guided by a small set of seed word pairs from a dictionary, without relying on additional knowledge or complex models.
摘要翻译：基于点击数据中的用户行为分析，提供Web查询翻译的方法和技术。这些方法和技术不但依赖于额外的知识或复杂的模型，而是从词典中产生由小型种子字对引导的大规模和及时的查询翻译对。

92. 发明授权

US08412665B2 Action prediction and identification temporal user behavior 有权
标题翻译：行动预测和识别临时用户行为
公开(公告)号：US08412665B2
公开(公告)日：2013-04-02
申请号：US12947871
申请日：2010-11-17
申请人： Gang Wang , Weizhu Chen , Zheng Chen , Zhikai Fan
发明人： Gang Wang , Weizhu Chen , Zheng Chen , Zhikai Fan
IPC分类号： G06F9/44 , G06N7/02 , G06N7/06
CPC分类号： G06N5/02 , G06F17/30693 , G06N5/043 , G06Q30/00 , G06Q30/0202
摘要： User behavior modeling can include determining temporal- or time-based actions performed by various users. From the mined temporal-based user actions, future actions can be predicted. Certain implementations include providing information and/or services based on the predicted future actions. Some implementations, include providing relevant information, services, and/or goods regarding the predicted future action.
摘要翻译：用户行为建模可以包括确定由各种用户执行的时间或时间的动作。从开采的基于时间的用户操作，可以预测未来的行动。某些实施方式包括基于预测的未来行动来提供信息和/或服务。一些实施方式包括提供有关预测未来行动的相关信息，服务和/或商品。

93. 发明申请

US20120143790A1 RELEVANCE OF SEARCH RESULTS DETERMINED FROM USER CLICKS AND POST-CLICK USER BEHAVIOR OBTAINED FROM CLICK LOGS 审中-公开
标题翻译：从用户点击确定的搜索结果的相关性和点击记录获得的点击后用户行为
公开(公告)号：US20120143790A1
公开(公告)日：2012-06-07
申请号：US12957692
申请日：2010-12-01
申请人： Gang Wang , Weizhu Chen , Zheng Chen
发明人： Gang Wang , Weizhu Chen , Zheng Chen
IPC分类号： G06N5/02 , G06F15/18
CPC分类号： G06N7/005 , G06F16/951
摘要： Data from a click log may be used to generate training data for a search engine. User click behavior and user post-click behavior may be used to assess the relevance of a page to a query. Labels for training data may be generated based on data from the click log. The labels may pertain to the relevance of a page to a query. For example, user post-click behavior that may be examined includes the amount of time that a user remains on a target page when a user clicks one of the search results.
摘要翻译：来自点击日志的数据可用于生成搜索引擎的训练数据。用户单击行为和用户点击后行为可用于评估页面与查询的相关性。可以根据点击日志的数据生成训练数据的标签。标签可能与页面与查询的相关性有关。例如，可以检查的用户点击后行为包括当用户单击其中一个搜索结果时用户保留在目标页面上的时间量。

94. 发明申请

US20100088303A1 MINING NEW WORDS FROM A QUERY LOG FOR INPUT METHOD EDITORS 有权
标题翻译：从输入法编辑器的查询记录中挖掘新的词
公开(公告)号：US20100088303A1
公开(公告)日：2010-04-08
申请号：US12244774
申请日：2008-10-03
申请人： Weizhu Chen , Qian Xun Li , Li Ju , Zheng Chen , Dong LI , Zhikai Fan
发明人： Weizhu Chen , Qian Xun Li , Li Ju , Zheng Chen , Dong LI , Zhikai Fan
IPC分类号： G06F17/30
CPC分类号： G06F17/30731
摘要： Described is a technology in which new words (including a phrase or set of Chinese characters) are mined from a query log. The new words may be added to (or otherwise supplement) an IME dictionary. A set of candidate queries may be selected from the log based upon market (e.g., the Chinese market) and/or by language. From this set, various filtering steps are performed to locate only new words that are frequently in used. For example, only frequent queries are kept for further processing, which may include filtering out queries based on length (e.g., less than two or greater than eight Chinese characters), and/or filtering out queries based on too many stop-words in the query. Processing may also include filtering out a query that is a substring of a larger query, or Vice-versa. Also described is Pinyin-based clustering and filtering, and filtering out queries already handled in the dictionary.
摘要翻译：描述了从查询日志中挖出新词（包括短语或一组汉字）的技术。新词可能会添加到（或以其他方式补充）IME词典。可以基于市场（例如，中国市场）和/或按语言从日志中选择一组候选查询。从该集合中，执行各种过滤步骤以仅定位经常使用的新词。例如，只有频繁的查询被保留用于进一步的处理，其可以包括基于长度（例如，少于两个或大于八个汉字）过滤掉查询，和/或基于过多的停止词过滤掉查询查询。处理还可以包括过滤掉作为较大查询的子串的查询，反之亦然。还描述了基于拼音的群集和过滤，并且过滤掉已经在字典中处理的查询。

95. 发明申请

US20080256444A1 Internet Visualization System and Related User Interfaces 有权
标题翻译：互联网可视化系统和相关用户界面
公开(公告)号：US20080256444A1
公开(公告)日：2008-10-16
申请号：US11972073
申请日：2008-01-10
申请人： Min Wang , Weizhu Chen , Benyu Zhang , Zheng Chen , Jian Wang
发明人： Min Wang , Weizhu Chen , Benyu Zhang , Zheng Chen , Jian Wang
IPC分类号： G06F3/00
CPC分类号： G06F17/30864 , G06F2216/03
摘要： Systems and methods are described for an Internet visualization system and related user interfaces. In one implementation, the system analyzes Internet search logs to determine most popular search queries across the world at a current time. A user interface displays a keyword of each of the most popular queries in a single visual display that relates each query to a geographical location of greatest popularity. The system can also filter queries according to demographics. In one implementation the user interface provides a 3-dimensional Internet visualization that adopts an ocean or seascape theme. The ocean floor displays a map of the world, and query bubbles rise from geographical locations on the map. The size and duration of each query bubble denotes the relative popularity of a given query.
摘要翻译：为互联网可视化系统和相关的用户界面描述了系统和方法。在一个实现中，系统分析互联网搜索日志以确定当前世界上最流行的搜索查询。用户界面在单个视觉显示中显示每个最流行的查询的关键字，其将每个查询与最受欢迎的地理位置相关联。该系统还可以根据人口特征来过滤查询。在一个实现中，用户界面提供采用海洋或海景主题的三维互联网可视化。海底显示世界地图，查询气泡从地图上的地理位置上升。每个查询气泡的大小和持续时间表示给定查询的相对受欢迎程度。

96. 发明申请

US20110302031A1 CLICK MODELING FOR URL PLACEMENTS IN QUERY RESPONSE PAGES 有权
标题翻译：点击建模查询响应页面中的网址
公开(公告)号：US20110302031A1
公开(公告)日：2011-12-08
申请号：US12795631
申请日：2010-06-07
申请人： Weizhu Chen , Gang Wang , Zheng Chen , Zhikai Fan , Thomas Minka
发明人： Weizhu Chen , Gang Wang , Zheng Chen , Zhikai Fan , Thomas Minka
IPC分类号： G06F15/18 , G06Q30/00 , G06N5/02
CPC分类号： G06Q30/02 , G06Q30/0255
摘要： A “General Click Model” (GCM) is constructed using a Bayesian network that is inherently capable of modeling “tail queries” by building the model on multiple attribute values that are shared across queries. More specifically, the GCM learns and predicts user click behavior towards URLs displayed on a query results page returned by a search engine. Unlike conventional click modeling approaches that learn models based on individual queries, the GCM learns click models from multiple attributes, with the influence of different attribute values being measured by Bayesian inference. This provides an advantage in learning that enables the GCM to achieve improved generalization and results, especially for tail queries, than conventional click models. In addition, most conventional click models consider only position and the identity of URLs when learning the model. In contrast, the GCM considers more session-specific attributes in making a final prediction for anticipated or expected user click behaviors.
摘要翻译：使用贝叶斯网络构建“通用点击模型”（GCM），该贝叶斯网络本质上能够通过在查询之间共享的多个属性值上构建模型来建模“尾部查询”。更具体地说，GCM学习并预测用户对搜索引擎返回的查询结果页面上显示的URL的点击行为。不同于传统的点击建模方法，基于个别查询的模型，GCM从多个属性学习点击模型，不同属性值的影响是通过贝叶斯推理来衡量的。这提供了学习的优势，使得GCM能够实现改进的泛化和结果，特别是尾部查询，而不是传统的点击模型。此外，大多数传统的点击模型只在学习模型时考虑URL的位置和身份。相比之下，GCM考虑更多的会话特定属性来对预期或预期的用户点击行为进行最终预测。

97. 发明申请

US20110295774A1 Training SVMs with Parallelized Stochastic Gradient Descent 有权
标题翻译：训练具有并行随机梯度下降的SVM
公开(公告)号：US20110295774A1
公开(公告)日：2011-12-01
申请号：US12790532
申请日：2010-05-28
申请人： Weizhu Chen , Gang Wang , Zheng Chen
发明人： Weizhu Chen , Gang Wang , Zheng Chen
IPC分类号： G06F15/18
CPC分类号： G06K9/6269 , G06N99/005
摘要： Techniques for training a non-linear support vector machine utilizing a stochastic gradient descent algorithm are provided. The computations of the stochastic gradient descent algorithm are parallelized via a number of processors. Calculations of the stochastic gradient descent algorithm on a particular processor may be combined according to a packing strategy before communicating the results of the calculations with the other processors.
摘要翻译：提供了利用随机梯度下降算法训练非线性支持向量机的技术。随机梯度下降算法的计算通过多个处理器并行化。在将计算结果与其他处理器通信之前，可以根据打包策略来组合特定处理器上的随机梯度下降算法。

98. 发明授权

US07870132B2 Constructing web query hierarchies from click-through data 有权
标题翻译：从点击型数据构建Web查询层次结构
公开(公告)号：US07870132B2
公开(公告)日：2011-01-11
申请号：US12020574
申请日：2008-01-28
申请人： Weizhu Chen , Benyu Zhang , Zheng Chen , Jian Wang , Dou Shen
发明人： Weizhu Chen , Benyu Zhang , Zheng Chen , Jian Wang , Dou Shen
IPC分类号： G06F17/30
CPC分类号： G06F17/30864
摘要： The claimed subject matter is directed to constructing query hierarchies in response to a query request. To construct a query hierarchy, a list of related candidate queries is generated in response to the received query request. The list of related candidate queries is generated by determining the relative coverage of information shared by the candidate queries and the query request. Relationships between the submitted query request and the candidate queries in the list are determined based upon the extent of relative coverage of information shared by the candidate queries and the query request. A query hierarchy is then constructed to reflect the determined relationships between the query request and the candidate queries.
摘要翻译：所要求保护的主题涉及响应于查询请求构建查询层次结构。为了构建查询层次结构，响应于接收的查询请求生成相关候选查询的列表。通过确定候选查询和查询请求共享的信息的相对覆盖率来生成相关候选查询的列表。基于候选查询和查询请求共享的信息的相对覆盖范围确定列表中提交的查询请求与候选查询之间的关系。然后构建查询层次结构以反映所确定的查询请求和候选查询之间的关系。

99. 发明申请

US20100161642A1 MINING TRANSLATIONS OF WEB QUERIES FROM WEB CLICK-THROUGH DATA 有权
标题翻译：从WEB点击数据挖掘网络查询的翻译
公开(公告)号：US20100161642A1
公开(公告)日：2010-06-24
申请号：US12342098
申请日：2008-12-23
申请人： Zheng Chen , Weizhu Chen
发明人： Zheng Chen , Weizhu Chen
IPC分类号： G06F17/30 , G06F17/28
CPC分类号： G06F17/30864 , G06F2216/03
摘要： Methods and technologies providing translations of web queries based on an analysis of user behavior in click-through data. These methods and technologies generates large-scale and timely query translation pairs guided by a small set of seed word pairs from a dictionary, without relying on additional knowledge or complex models.
摘要翻译：基于点击数据中的用户行为分析，提供Web查询翻译的方法和技术。这些方法和技术不但依赖于额外的知识或复杂的模型，而是从词典中产生由小型种子字对引导的大规模和及时的查询翻译对。

100. 发明申请

US20090132530A1 WEB CONTENT MINING OF PAIR-BASED DATA 有权
标题翻译：基于对象数据的WEB内容采集
公开(公告)号：US20090132530A1
公开(公告)日：2009-05-21
申请号：US11941968
申请日：2007-11-19
申请人： Weizhu Chen , Long Jiang , Ming Zhou , Benyu Zhang , Zheng Chen , Jian Wang
发明人： Weizhu Chen , Long Jiang , Ming Zhou , Benyu Zhang , Zheng Chen , Jian Wang
IPC分类号： G06F17/30
CPC分类号： G06F17/30864
摘要： Described herein is technology for, among other things, mining pair-based data on the web. The technology involves an online pair-based data mining system as well as an offline SVM training system. By subjecting a pair-based input data to the systems, one may grow a pool of pair-based data which share characteristics of the pair-based input data in more efficient manner.
摘要翻译：这里描述的是用于在网络上挖掘基于对的数据的技术。该技术涉及一个在线的基于对的数据挖掘系统以及离线SVM培训系统。通过对基于对的输入数据进行系统的处理，可以以更有效的方式增加基于成对的输入数据的特征的基于对的数据池。

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