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61. 发明授权

US07590603B2 Method and system for classifying and identifying messages as question or not a question within a discussion thread 失效
标题翻译：用于将消息分类和识别为问题的方法和系统，或不是讨论线程中的问题
公开(公告)号：US07590603B2
公开(公告)日：2009-09-15
申请号：US10957329
申请日：2004-10-01
申请人： Benyu Zhang , Zheng Chen , Hua-Jun Zeng , Wei-Ying Ma
发明人： Benyu Zhang , Zheng Chen , Hua-Jun Zeng , Wei-Ying Ma
IPC分类号： G06F15/18
CPC分类号： G06F17/30707
摘要： A method and system for classifying messages of a discussion thread as questions is provided. A classification system generates a classifier to classify messages of discussion threads as question messages or non-question messages. The system trains the classifier using the feature vectors and input classifications derived from a training set of discussion threads. After the classifier is trained, the classification system uses the classifier to classify messages within a corpus of discussion threads as question or non-question messages. To classify a message, the classification system generates a feature vector for the messages and submits that feature vector to the classifier. The classifier generates a score for the message indicating a likelihood that the message is a question message.
摘要翻译：提供了一种用于将讨论线程的消息分类为问题的方法和系统。分类系统生成分类器以将讨论线程的消息分类为问题消息或非问题消息。系统使用从训练集讨论线程派生的特征向量和输入分类来训练分类器。在分类器训练之后，分类系统使用分类器将讨论线程的语料库中的消息分类为问题或非问题消息。为了对消息进行分类，分类系统生成消息的特征向量，并将该特征向量提交给分类器。分类器生成消息的分数，指示消息是问题消息的可能性。

62. 发明申请

US20070208728A1 Predicting demographic attributes based on online behavior 审中-公开
标题翻译：基于在线行为预测人口统计特征
公开(公告)号：US20070208728A1
公开(公告)日：2007-09-06
申请号：US11366526
申请日：2006-03-03
申请人： Benyu Zhang , Honghua Dai , Hua-Jun Zeng , Li Qi , Tarek Najm , Teresa Mah , Vladimir Shipunov , Ying Li , Zheng Chen
发明人： Benyu Zhang , Honghua Dai , Hua-Jun Zeng , Li Qi , Tarek Najm , Teresa Mah , Vladimir Shipunov , Ying Li , Zheng Chen
IPC分类号： G06F17/30
CPC分类号： G06F16/337 , G06F16/951
摘要： This invention provides a system and method for predicting user demographic attributes for non-registered users and users with incomplete profiles. The invention uses demographic information from registered users and user search history logs to create a database of information that associates the users' search history habits with their demographic attributes. The invention creates a first database that associates users' search query history with their demographic attributes, and also creates a second database that associates web pages that users have visited frequently along with the users' demographic attributes. The invention can compare the searching and browsing habits of non-registered users and users with incomplete profiles to the searching and browsing habits of registered users. Through the comparison, the invention can use the corresponding demographic attributes of the registered users to predict the demographic attributes of the non-registered users and the registered users with incomplete profiles.
摘要翻译：本发明提供一种用于预测非注册用户和具有不完整简档的用户的用户人口统计属性的系统和方法。本发明使用来自注册用户和用户搜索历史日志的人口统计信息来创建将用户的搜索历史习惯与其人口统计属性相关联的信息数据库。本发明创建了将用户的搜索查询历史与其人口统计属性相关联的第一数据库，并且还创建了将用户经常访问的网页与用户的人口统计属性一起关联的第二数据库。本发明可以将注册用户和注册用户不完整的用户的搜索和浏览习惯与注册用户的搜索和浏览习惯进行比较。通过比较，本发明可以使用注册用户的相应人口统计特性来预测非注册用户和具有不完整简档的注册用户的人口统计属性。

63. 发明申请

US20070192164A1 Generation of contextual image-containing advertisements 有权
标题翻译：生成含上下文图像的广告
公开(公告)号：US20070192164A1
公开(公告)日：2007-08-16
申请号：US11355634
申请日：2006-02-15
申请人： Shuzhen Nong , Ying Li , Tarek Najm , Li Li , Zheng Chen , Hua-Jun Zeng , Benyu Zhang , Yin Li , Dean Carignan , Ying-Qing Xu
发明人： Shuzhen Nong , Ying Li , Tarek Najm , Li Li , Zheng Chen , Hua-Jun Zeng , Benyu Zhang , Yin Li , Dean Carignan , Ying-Qing Xu
IPC分类号： G07G1/00 , H04N7/10
CPC分类号： G06Q30/02
摘要： According to embodiments of the invention, an advertisement-generation system generates image-containing advertisements. The advertisement-generation system includes: at least one feature-selection guideline that specifies at least one recommended feature for image-containing advertisements based on advertiser inputs that specify at least one of advertisement-target-audience information, cost information, and advertiser-industry information; an image-clip library from which images are selected for inclusion in the image-containing advertisements; and at least one advertisement template that is based on the at least one feature-selection guideline; wherein the system automatically generates image-containing advertisements that contain one or more suggested colors that are automatically suggested based on one or more colors present on a web page that will host the image-containing advertisement.
摘要翻译：根据本发明的实施例，广告生成系统生成包含图像的广告。广告生成系统包括：至少一个特征选择指南，其基于广告商输入指定至少一个推荐的用于图像的广告的特征，其指定广告目标受众信息，成本信息和广告商行业中的至少一个信息; 选择图像以包含在包含图像的广告中的图像剪辑库; 以及至少一个基于所述至少一个特征选择指南的广告模板; 其中所述系统自动生成包含一个或多个建议的颜色的图像包含广告，所述一个或多个建议的颜色是基于存在于将承载含图像的广告的网页上的一种或多种颜色而自动建议的。

64. 发明申请

US20050234955A1 Clustering based text classification 有权
标题翻译：基于聚类的文本分类
公开(公告)号：US20050234955A1
公开(公告)日：2005-10-20
申请号：US10921477
申请日：2004-08-16
申请人： Hua-Jun Zeng , Xuanhui Wang , Zheng Chen , Benyu Zhang , Wei-Ying Ma
发明人： Hua-Jun Zeng , Xuanhui Wang , Zheng Chen , Benyu Zhang , Wei-Ying Ma
IPC分类号： G06F17/30
CPC分类号： G06F17/3071
摘要： Systems and methods for clustering-based text classification are described. In one aspect text is clustered as a function of labeled data to generate cluster(s). The text includes the labeled data and unlabeled data. Expanded labeled data is then generated as a function of the cluster(s). The expanded label data includes the labeled data and at least a portion of unlabeled data. Discriminative classifier(s) are then trained based on the expanded labeled data and remaining ones of the unlabeled data.
摘要翻译：描述了基于聚类的文本分类的系统和方法。在一个方面，文本被聚类为标记数据的函数以生成集群。该文本包括标记数据和未标记数据。然后根据集群生成扩展标签数据。扩展的标签数据包括标记的数据和至少一部分未标记的数据。然后基于扩展的标记数据和剩余的未标记数据来训练鉴别分类器。

65. 发明申请

US20050234952A1 Content propagation for enhanced document retrieval 失效
标题翻译：增强文档检索的内容传播
公开(公告)号：US20050234952A1
公开(公告)日：2005-10-20
申请号：US10826161
申请日：2004-04-15
申请人： Hua-Jun Zeng , Benyu Zhang , Zheng Chen , Wei-Ying Ma , Hsiao-Wuen Hon , Daniel Cook , Gabor Hirschler , Karen Fries , Kurt Samuelson
发明人： Hua-Jun Zeng , Benyu Zhang , Zheng Chen , Wei-Ying Ma , Hsiao-Wuen Hon , Daniel Cook , Gabor Hirschler , Karen Fries , Kurt Samuelson
IPC分类号： G06F19/00 , G06F17/30
CPC分类号： G06F17/30631 , G06F17/30722 , G06F17/30864 , Y10S707/99935 , Y10S707/99942
摘要： Systems and methods providing computer-implemented content propagation for enhanced document retrieval are described. In one aspect, reference information directed to one or more documents is identified. The reference information is identified from one or more sources of data that are independent of a data source that includes the one or more documents. Metadata that is proximally located to the reference information is extracted from the one or more sources of data. Relevance between respective features of the metadata to content of associated ones of the one or more documents is calculated. For each document of the one or more documents, associated portions of the metadata is indexed with the relevance of features from the respective portions into original content of the document. The indexing generates one or more enhanced documents.
摘要翻译：描述了提供用于增强文档检索的计算机实现的内容传播的系统和方法。在一个方面，指定针对一个或多个文档的参考信息。参考信息从一个或多个独立于包括一个或多个文档的数据源的数据来源识别。从一个或多个数据来源提取近端位于参考信息的元数据。计算元数据的各个特征与一个或多个文档中相关联的内容的相关性。对于一个或多个文档的每个文档，将元数据的关联部分与来自相应部分的特征与文档的原始内容的相关性进行索引。索引生成一个或多个增强文档。

66. 发明授权

US07747618B2 Augmenting user, query, and document triplets using singular value decomposition 失效
标题翻译：使用奇异值分解增强用户，查询和文档三元组
公开(公告)号：US07747618B2
公开(公告)日：2010-06-29
申请号：US11222243
申请日：2005-09-08
申请人： Hua-Jun Zeng , Jian-Tao Sun , Wei-Ying Ma , Zheng Chen , Benyu Zhang , Huan Liu
发明人： Hua-Jun Zeng , Jian-Tao Sun , Wei-Ying Ma , Zheng Chen , Benyu Zhang , Huan Liu
IPC分类号： G06F7/00
CPC分类号： G06F17/30675 , G06F17/30864
摘要： A system for augmenting click-through data with latent information present in the click-through data for use in generating search results that are better tailored to the information needs of a user submitting a query is provided. The augmentation system creates a three-dimensional matrix with the dimensions of users, queries, and documents. The augmentation system then performs a three-order singular value decomposition of the three-dimensional matrix to generate a three-dimensional core singular value matrix and a left singular matrix for each dimension. The augmentation system finally multiplies the three-dimensional core singular value matrix by the left singular matrices to generate an augmented three-dimensional matrix that explicitly contains the information that was latent in the un-augmented three-dimensional matrix.
摘要翻译：提供了一种用于通过存在于点击数据中的潜在信息来增强点击数据的系统，用于生成针对提交查询的用户的信息需求更好地定制的搜索结果。增强系统创建一个具有用户，查询和文档尺寸的三维矩阵。然后，增强系统执行三维矩阵的三阶奇异值分解，以产生每个维度的三维核心奇异值矩阵和左奇异矩阵。增强系统最终将三维核心奇异值矩阵乘以左奇异矩阵，以生成明确包含未增强三维矩阵中潜在信息的增强三维矩阵。

67. 发明授权

US07698339B2 Method and system for summarizing a document 有权
标题翻译：汇总文件的方法和系统
公开(公告)号：US07698339B2
公开(公告)日：2010-04-13
申请号：US10918242
申请日：2004-08-13
申请人： Benyu Zhang , Wei-Ying Ma , Zheng Chen , Hua-Jun Zeng , Dou Shen
发明人： Benyu Zhang , Wei-Ying Ma , Zheng Chen , Hua-Jun Zeng , Dou Shen
IPC分类号： G06F17/30
CPC分类号： G06F17/30705 , G06F17/30719
摘要： A method and system for calculating the significance of a sentence within a document is provided. The summarization system calculates the significance of the sentences of a document and selects the most significant sentences as the summary of the document. The summarization system calculates the significance of a sentence based on the “important” words of the document that are contained within the sentence. The summarization system calculates the importance of words of the document using various scoring techniques and then combines the scores to classify a word as important or not important. The summarization system can then be used to identify significant sentences of the document based on the important words that a sentence contains and select significant sentences as a summary of the document.
摘要翻译：提供了一种用于计算文档中句子的重要性的方法和系统。总结系统计算文档的句子的重要性，并选择最重要的句子作为文档的摘要。总结系统根据文本中包含的“重要”字来计算句子的意义。总结系统使用各种评分技术计算文档的单词的重要性，然后将分数组合成一个单词重要或不重要。然后，总结系统可以用于基于句子包含的重要词语来识别文档的重要句子，并且将重要句子作为文档的摘要来选择。

68. 发明授权

US07630976B2 Method and system for adapting search results to personal information needs 失效
标题翻译：将搜索结果适应个人信息需求的方法和系统
公开(公告)号：US07630976B2
公开(公告)日：2009-12-08
申请号：US11125839
申请日：2005-05-10
申请人： Benyu Zhang , Gui-Rong Xue , Hua-Jun Zeng , Wei-Ying Ma , Xue-Mei Jiang , Zheng Chen
发明人： Benyu Zhang , Gui-Rong Xue , Hua-Jun Zeng , Wei-Ying Ma , Xue-Mei Jiang , Zheng Chen
IPC分类号： G06F17/30 , G06Q30/00
CPC分类号： G06F17/30882 , G06F17/30867 , Y10S707/99935
摘要： A method and system for adapting search results of a query to the information needs of the user submitting the query is provided. A search system analyzes click-through triplets indicating that a user submitted a query and that the user selected a document from the results of the query. To overcome the large size and sparseness of the click-through data, the search system when presented with an input triplet comprising a user, a query, and a document determines a probability that the user will find the input document important by smoothing the click-through triplets. The search system then orders documents of the result based on the probability of their importance to the input user.
摘要翻译：提供了一种用于将查询的搜索结果适应于提交查询的用户的信息需求的方法和系统。搜索系统分析点击三胞胎，指示用户提交了查询，并且用户从查询的结果中选择了文档。为了克服点击数据的大尺寸和稀疏性，搜索系统当呈现包括用户，查询和文档的输入三元组时，确定用户将通过平滑点击数据来重新找到输入文档的概率，通过三胞胎。然后，搜索系统基于其对输入用户的重要性的概率来订购结果的文档。

69. 发明授权

US07533094B2 Method and system for determining similarity of items based on similarity objects and their features 有权
标题翻译：基于相似对象及其特征确定项目相似度的方法和系统
公开(公告)号：US07533094B2
公开(公告)日：2009-05-12
申请号：US10997749
申请日：2004-11-23
申请人： Benyu Zhang , Hua-Jun Zeng , Wei-Ying Ma , Zheng Chen , Ning Liu , Jun Yan
发明人： Benyu Zhang , Hua-Jun Zeng , Wei-Ying Ma , Zheng Chen , Ning Liu , Jun Yan
IPC分类号： G06F17/30
CPC分类号： G06F17/3069 , Y10S707/99934 , Y10S707/99935 , Y10S707/99936 , Y10S707/99937
摘要： A method and system for determining similarity between items is provided. To calculate similarity scores for pairs of items, the similarity system initializes a similarity score for each pair of objects and each pair of features. The similarity system then iteratively calculates the similarity scores for each pair of objects based on the similar scores of the pairs of features calculated during a previous iteration and calculates the similarity scores for each pair of features based on the similarity scores of the pairs of objects calculated during a previous iteration. The similarity system implements an algorithm that is based on a recursive definition of the similarities between objects and between features. The similarity system continues the iterations of recalculating the similarity scores until the similarity scores converge on a solution.
摘要翻译：提供了一种用于确定项目之间的相似性的方法和系统。为了计算物品对的相似性分数，相似系统初始化每对物体和每对特征的相似性得分。然后，相似系统基于在先前迭代期间计算的特征对的类似得分迭代地计算每对对象的相似性得分，并且基于计算出的对象对的相似性得分来计算每对特征的相似性得分在之前的迭代。相似系统实现了一种基于对象之间和特征之间的相似性的递归定义的算法。相似系统继续重新计算相似性分数的迭代，直到相似性得分收敛于解。

70. 发明授权

US07502495B2 Method and system for incrementally learning an adaptive subspace by optimizing the maximum margin criterion 有权
标题翻译：通过优化最大裕度标准来逐步学习自适应子空间的方法和系统
公开(公告)号：US07502495B2
公开(公告)日：2009-03-10
申请号：US11070382
申请日：2005-03-01
申请人： Benyu Zhang , Hua-Jun Zeng , Jun Yan , Wei-Ying Ma , Zheng Chen
发明人： Benyu Zhang , Hua-Jun Zeng , Jun Yan , Wei-Ying Ma , Zheng Chen
IPC分类号： G06K9/00
CPC分类号： G06K9/6234
摘要： A method and system for generating a projection matrix for projecting data from a high dimensional space to a low dimensional space. The system establishes an objective function based on a maximum margin criterion matrix. The system then provides data samples that are in the high dimensional space and have a class. For each data sample, the system incrementally derives leading eigenvectors of the maximum margin criterion matrix based on the derivation of the leading eigenvectors of the last data sample. The derived eigenvectors compose the projection matrix, which can be used to project data samples in a high dimensional space into a low dimensional space.
摘要翻译：一种用于生成用于将数据从高维空间投影到低维空间的投影矩阵的方法和系统。该系统基于最大裕度标准矩阵建立目标函数。然后，系统提供处于高维空间并具有类的数据样本。对于每个数据样本，系统基于最后数据样本的前导特征向量的推导，递增地导出最大边际准则矩阵的前导特征向量。衍生的特征向量组成投影矩阵，可用于将高维空间中的数据样本投影到低维空间中。

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