公开(公告)号：US20050234879A1

公开(公告)日：2005-10-20

申请号：US10825894

申请日：2004-04-15

申请人： Hua-Jun Zeng ,  Benyu Zhang ,  Zheng Chen ,  Wei-Ying Ma ,  Li Li ,  Ying Li ,  Tarek Najm

发明人： Hua-Jun Zeng ,  Benyu Zhang ,  Zheng Chen ,  Wei-Ying Ma ,  Li Li ,  Ying Li ,  Tarek Najm

IPC分类号： G06F17/30 ,  G06F7/00

CPC分类号： G06F17/30864 ,  G06F17/3064 ,  Y10S707/99933 ,  Y10S707/99934 ,  Y10S707/99935 ,  Y10S707/99936 ,  Y10S707/99937

摘要： Systems and methods for related term suggestion are described. In one aspect, term clusters are generated as a function of calculated similarity of term vectors. Each term vector having been generated from search results associated with a set of high frequency of occurrence (FOO) historical queries previously submitted to a search engine. Responsive to receiving a term/phrase from an entity, the term/phrase is evaluated in view of terms/phrases in the term clusters to identify one or more related term suggestions.

摘要翻译： 描述相关术语建议的系统和方法。 在一个方面，产生术语簇作为计算的项目向量相似度的函数。 从与先前提交给搜索引擎的一组高频率（FOO）历史查询相关联的搜索结果生成每个词向量。 响应于从实体接收术语/短语，根据术语集合中的术语/短语来评估术语/短语以识别一个或多个相关术语建议。

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。

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。

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。

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。

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。

公开(公告)号：US07366705B2

公开(公告)日：2008-04-29

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： G06E1/00 ,  G06E3/00 ,  G06F15/18 ,  G06G7/00

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。

公开(公告)号：US20070143176A1

公开(公告)日：2007-06-21

申请号：US11300918

申请日：2005-12-15

申请人： Shuzhen Nong ,  Ying Li ,  Tarek Najm ,  Li Li ,  Hua-Jun Zeng ,  Zheng Chen ,  Benyu Zhang

发明人： Shuzhen Nong ,  Ying Li ,  Tarek Najm ,  Li Li ,  Hua-Jun Zeng ,  Zheng Chen ,  Benyu Zhang

IPC分类号： G06Q30/00

CPC分类号： G06Q30/02 ,  G06F17/30864 ,  G06Q30/0251 ,  G06Q30/0275

摘要： Seed keywords are leveraged to provide expanded keywords that are then associated with relevant advertisers. Instances can also include locating potential advertisers based on the expanded keywords. Inverse lookup techniques are employed to determine which keywords are associated with an advertiser. Filtering can then be employed to eliminate inappropriate keywords for that advertiser. The keywords are then automatically revealed to the advertiser for consideration as relevant search terms for their advertisements. In this manner, revenue for a search engine and/or for an advertiser can be substantially enhanced through the automatic expansion of relevant search terms. Advertisers also benefit by having larger and more relevant search term selections automatically available to them, saving them both time and money.

摘要翻译： 使用种子关键字来提供扩展的关键字，然后与相关的广告商相关联。 实例还可以包括根据扩展的关键字定位潜在的广告客户。 采用反向查找技术来确定哪些关键字与广告商相关联。 然后可以使用过滤来消除该广告客户的不合适的关键字。 然后，这些关键字会自动向广告客户显示，作为其广告的相关搜索字词。 以这种方式，可以通过自动扩展相关搜索词来大大增强搜索引擎和/或广告商的收入。 广告商也可以通过自动获得更大更多相关的搜索词选项来获益，从而节省时间和金钱。

公开(公告)号：US07194466B2

公开(公告)日：2007-03-20

申请号：US10427548

申请日：2003-05-01

申请人： Zheng Chen ,  Ji-Dong Wang ,  Hua-Jun Zeng ,  Xiaoming Sun ,  Li Tao ,  Wei-Ying Ma

发明人： Zheng Chen ,  Ji-Dong Wang ,  Hua-Jun Zeng ,  Xiaoming Sun ,  Li Tao ,  Wei-Ying Ma

IPC分类号： G06F17/30

CPC分类号： G06F17/30707 ,  G06K9/6218 ,  Y10S707/99936 ,  Y10S707/99937 ,  Y10S707/99943 ,  Y10S707/99945

摘要： One aspect relates to clustering a group of objects of a first object type based on a relative importance using links extending between objects of the first object type and certain objects of the second object type. In one embodiment, the first object type is a Web page object type and the second type is a user object type.

摘要翻译： 一方面涉及使用在第一对象类型的对象和第二对象类型的特定对象之间延伸的链接基于相对重要性来聚集第一对象类型的对象组。 在一个实施例中，第一对象类型是网页对象类型，第二类型是用户对象类型。

公开(公告)号：US20070055646A1

公开(公告)日：2007-03-08

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

发明人： Hua-Jun Zeng ,  Jian-Tao Sun ,  Wei-Ying Ma ,  Zheng Chen ,  Benyu Zhang

IPC分类号： G06F17/30

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。