公开(公告)号：US09195942B2

公开(公告)日：2015-11-24

申请号：US12406039

申请日：2009-03-17

申请人： Benyu Zhang ,  Wei-Ying Ma ,  Gu Xu ,  Hongbin Gao ,  Zheng Chen ,  Randy Hinrichs ,  Hua-Jun Zeng

发明人： Benyu Zhang ,  Wei-Ying Ma ,  Gu Xu ,  Hongbin Gao ,  Zheng Chen ,  Randy Hinrichs ,  Hua-Jun Zeng

IPC分类号： G06F17/30 ,  G06N5/02

CPC分类号： G06N5/022 ,  G06F17/30616 ,  Y10S707/99933 ,  Y10S707/99934 ,  Y10S707/99935

摘要： A method and system for identifying information about people is provided. The information system identifies groups of people that have relationships based on their relationships to documents or more generally to objects. The information system initially is provided with an indication of which people have which relationships to which documents. The information system then identifies clusters of people based on having a relationship to the same objects. The information system may also identify clusters of related objects associated with a cluster of people. When a user wants to identify information about a person, the user can provide the name of that person to the information system. The information system then can retrieve and display the names of the other people who are in the same cluster as the person.

公开(公告)号：US08112268B2

公开(公告)日：2012-02-07

申请号：US12254796

申请日：2008-10-20

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

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

IPC分类号： G06F17/28

CPC分类号： G06F17/30

摘要： A method and system for prioritizing communications based on classifications of sentences within the communications is provided. A sentence classification system may classify sentences of communications according to various classifications such as “sentence mode.” The sentence classification system trains a sentence classifier using training data and then classifies sentences using the trained sentence classifier. After the sentences of a communication are classified, a document ranking system may generate a rank for the communication based on the classifications of the sentences within the communication. The document ranking system trains a document rank classifier using training data and then calculates the rank of communications using the trained document rank classifier.

摘要翻译： 提供了一种基于通信内的句子分类来优先化通信的方法和系统。 句子分类系统可以根据诸如“句子模式”的各种分类对通信句进行分类。句子分类系统使用训练数据训练句子分类器，然后使用训练句子分类器对句子进行分类。 在对通信的句子进行分类之后，文档排序系统可以基于通信中的句子的分类来生成用于通信的等级。 文档排序系统使用训练数据训练文档排序分类器，然后使用经过训练的文档排序分类器来计算通信的等级。

公开(公告)号：US07707129B2

公开(公告)日：2010-04-27

申请号：US11384889

申请日：2006-03-20

申请人： Dong Zhuang ,  Benyu Zhang ,  Zheng Chen ,  Hua-Jun Zeng ,  Jian Wang

发明人： Dong Zhuang ,  Benyu Zhang ,  Zheng Chen ,  Hua-Jun Zeng ,  Jian Wang

IPC分类号： G06F15/18 ,  G06E1/00 ,  G06E3/00

CPC分类号： G06F17/30707 ,  G06K9/6269

摘要： Embodiments of the invention relate to improvements to the support vector machine (SVM) classification model. When text data is significantly unbalanced (i.e., positive and negative labeled data are in disproportion), the classification quality of standard SVM deteriorates. Embodiments of the invention are directed to a weighted proximal SVM (WPSVM) model that achieves substantially the same accuracy as the traditional SVM model while requiring significantly less computational time. A weighted proximal SVM (WPSVM) model in accordance with embodiments of the invention may include a weight for each training error and a method for estimating the weights, which automatically solves the unbalanced data problem. And, instead of solving the optimization problem via the KKT (Karush-Kuhn-Tucker) conditions and the Sherman-Morrison-Woodbury formula, embodiments of the invention use an iterative algorithm to solve an unconstrained optimization problem, which makes WPSVM suitable for classifying relatively high dimensional data.

摘要翻译： 本发明的实施例涉及对支持向量机（SVM）分类模型的改进。 当文本数据显着不平衡（即正负标签数据不成比例）时，标准SVM的分类质量恶化。 本发明的实施例涉及一种加权近端SVM（WPSVM）模型，其实现与传统SVM模型基本相同的精度，同时需要显着更少的计算时间。 根据本发明的实施例的加权近端SVM（WPSVM）模型可以包括每个训练误差的权重和用于估计权重的方法，其自动地解决不平衡数据问题。 而且，不是通过KKT（Karush-Kuhn-Tucker）条件和Sherman-Morrison-Woodbury公式来解决优化问题，而是本发明的实施例使用迭代算法来解决无约束优化问题，这使得WPSVM适合于相对分类 高维数据。

公开(公告)号：US07664735B2

公开(公告)日：2010-02-16

申请号：US10837540

申请日：2004-04-30

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： G06F17/00

CPC分类号： G06F17/30867 ,  Y10S707/99933

摘要： A method and system for ranking documents of search results based on information richness and diversity of topics. A ranking system determines the information richness of each document within a search result. The ranking system groups documents of a search result based on their relatedness, meaning that they are directed to similar topics. The ranking system ranks the documents to ensure that the highest ranking documents may include at least one document covering each topic, that is, one document from each of the groups. The ranking system selects the document from each group that has the highest information richness of the documents within the group. When the documents are presented to a user in rank order, the user will likely find on the first page of the search result documents that cover a variety of topics, rather than just a single popular topic.

摘要翻译： 基于信息丰富性和主题多样性对搜索结果文档进行排序的方法和系统。 排名系统确定搜索结果内每个文档的信息丰富度。 排名系统根据其相关性对搜索结果的文档进行分组，这意味着它们针对类似的主题。 排名系统排列文件，以确保最高排名的文档可能包含至少一个涵盖每个主题的文档，即每个组中的一个文档。 排名系统选择组内文件信息丰富度最高的组中的文档。 当文件以等级顺序呈现给用户时，用户可能会在搜索结果文档的第一页上找到涵盖各种主题的文档，而不仅仅是一个流行的主题。

公开(公告)号：US20090313706A1

公开(公告)日：2009-12-17

申请号：US12510186

申请日：2009-07-27

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

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

IPC分类号： G06F17/30 ,  G06F11/00 ,  G06F12/14 ,  G06F12/16 ,  G06F7/04 ,  G06F21/00 ,  G06F7/00 ,  G08B23/00 ,  H04N7/16

CPC分类号： G06F17/30616 ,  G06F17/30628 ,  G06F17/30678 ,  G06F21/6245 ,  H04L51/12 ,  Y10S707/99933

摘要： A method and system for detecting whether an outgoing communication contains confidential information or other target information is provided. The detection system is provided with a collection of documents that contain confidential information, referred to as “confidential documents.” When the detection system is provided with an outgoing communication, it compares the content of the outgoing communication to the content of the confidential documents. If the outgoing communication contains confidential information, then the detection system may prevent the outgoing communication from being sent outside the organization. The detection system detects confidential information based on the similarity between the content of an outgoing communication and the content of confidential documents that are known to contain confidential information.

摘要翻译： 提供一种用于检测输出通信是否包含机密信息或其他目标信息的方法和系统。 检测系统提供了一系列包含机密信息的文件，称为“机密文件”。 当向检测系统提供传出通信时，将传出通信的内容与机密文档的内容进行比较。 如果传出通信包含机密信息，则检测系统可以防止传出通信被发送到组织外部。 检测系统基于传出通信的内容与已知包含机密信息的机密文档的内容之间的相似性来检测机密信息。

公开(公告)号：US07617176B2

公开(公告)日：2009-11-10

申请号：US10889841

申请日：2004-07-13

申请人： Hua-Jun Zeng ,  Qicai He ,  Guimei Liu ,  Zheng Chen ,  Benyu Zhang ,  Wei-Ying Ma

发明人： Hua-Jun Zeng ,  Qicai He ,  Guimei Liu ,  Zheng Chen ,  Benyu Zhang ,  Wei-Ying Ma

IPC分类号： G06F7/00

CPC分类号： G06F17/3071 ,  G06F17/30864 ,  Y10S707/99931

摘要： A clustering architecture that dynamically groups the search result documents into clusters labeled by phrases extracted from the search result snippets. Documents related to the same topic usually share a common vocabulary. The words are first clustered based on their co-occurrences and each cluster forms a potentially interesting topic. Keywords are chosen and then clustered by counting co-occurrences of pairs of keywords. Documents are assigned to relevant topics based on the feature vectors of the clusters.

摘要翻译： 将搜索结果文档动态地分组到由从搜索结果片段中提取的短语标签的聚类体系结构。 与同一主题相关的文件通常共享一个共同的词汇。 这些单词首先基于它们的共同出现而聚集，并且每个集合形成潜在有趣的主题。 选择关键词，然后通过计算关键字对的共同出现来聚类。 基于集群的特征向量将文档分配给相关主题。

公开(公告)号：US20090228452A1

公开(公告)日：2009-09-10

申请号：US12406039

申请日：2009-03-17

申请人： Benyu Zhang ,  Wei-Ying Ma ,  Gu Xu ,  Hongbin Gao ,  Zheng Chen ,  Randy Hinrichs ,  Hua-Jun Zeng

发明人： Benyu Zhang ,  Wei-Ying Ma ,  Gu Xu ,  Hongbin Gao ,  Zheng Chen ,  Randy Hinrichs ,  Hua-Jun Zeng

IPC分类号： G06F17/30

CPC分类号： G06N5/022 ,  G06F17/30616 ,  Y10S707/99933 ,  Y10S707/99934 ,  Y10S707/99935

摘要： A method and system for identifying information about people is provided. The information system identifies groups of people that have relationships based on their relationships to documents or more generally to objects. The information system initially is provided with an indication of which people have which relationships to which documents. The information system then identifies clusters of people based on having a relationship to the same objects. The information system may also identify clusters of related objects associated with a cluster of people. When a user wants to identify information about a person, the user can provide the name of that person to the information system. The information system then can retrieve and display the names of the other people who are in the same cluster as the person.

摘要翻译： 提供了一种用于识别人的信息的方法和系统。 信息系统根据与文档的关系或更一般地与对象的关系来识别具有关系的人群。 信息系统最初被提供指示哪些人与哪些文档有哪些关系。 然后，信息系统基于与相同对象的关系来识别人群。 信息系统还可以识别与一群人相关联的相关对象的群集。 当用户想要识别关于人的信息时，用户可以向该信息系统提供该人的姓名。 然后，信息系统可以检索和显示与该人在同一集群中的其他人的姓名。

公开(公告)号：US07392474B2

公开(公告)日：2008-06-24

申请号：US10836319

申请日：2004-04-30

申请人： Zheng Chen ,  Dou Shen ,  Benyu Zhang ,  Hua-Jun Zeng ,  Wei-Ying Ma

发明人： Zheng Chen ,  Dou Shen ,  Benyu Zhang ,  Hua-Jun Zeng ,  Wei-Ying Ma

IPC分类号： G06F17/00

CPC分类号： G06F17/30719 ,  G06F17/30864

摘要： A method and system for classifying display pages based on automatically generated summaries of display pages. A web page classification system uses a web page summarization system to generate summaries of web pages. The summary of a web page may include the sentences of the web page that are most closely related to the primary topic of the web page. The summarization system may combine the benefits of multiple summarization techniques to identify the sentences of a web page that represent the primary topic of the web page. Once the summary is generated, the classification system may apply conventional classification techniques to the summary to classify the web page. The classification system may use conventional classification techniques such as a Naïve Bayesian classifier or a support vector machine to identify the classifications of a web page based on the summary generated by the summarization system.

摘要翻译： 一种基于自动生成的显示页面摘要来分类显示页面的方法和系统。 网页分类系统使用网页摘要系统来生成网页摘要。 网页的摘要可以包括与网页的主要主题最密切相关的网页的句子。 总结系统可以结合多个汇总技术的优点来识别代表网页的主要主题的网页的句子。 一旦生成摘要，分类系统可以将常规分类技术应用于摘要以对网页进行分类。 分类系统可以使用诸如朴素贝叶斯分类器或支持向量机的常规分类技术来基于由汇总系统生成的摘要来识别网页的分类。

公开(公告)号：US20070239638A1

公开(公告)日：2007-10-11

申请号：US11384889

申请日：2006-03-20

申请人： Dong Zhuang ,  Benyu Zhang ,  Zheng Chen ,  Hua-Jun Zeng ,  Jian Wang

发明人： Dong Zhuang ,  Benyu Zhang ,  Zheng Chen ,  Hua-Jun Zeng ,  Jian Wang

IPC分类号： G06F15/18

CPC分类号： G06F17/30707 ,  G06K9/6269

摘要： Embodiments of the invention relate to improvements to the support vector machine (SVM) classification model. When text data is significantly unbalanced (i.e., positive and negative labeled data are in disproportion), the classification quality of standard SVM deteriorates. Embodiments of the invention are directed to a weighted proximal SVM (WPSVM) model that achieves substantially the same accuracy as the traditional SVM model while requiring significantly less computational time. A weighted proximal SVM (WPSVM) model in accordance with embodiments of the invention may include a weight for each training error and a method for estimating the weights, which automatically solves the unbalanced data problem. And, instead of solving the optimization problem via the KKT (Karush-Kuhn-Tucker) conditions and the Sherman-Morrison-Woodbury formula, embodiments of the invention use an iterative algorithm to solve an unconstrained optimization problem, which makes WPSVM suitable for classifying relatively high dimensional data.

摘要翻译： 本发明的实施例涉及对支持向量机（SVM）分类模型的改进。 当文本数据显着不平衡（即正负标签数据不成比例）时，标准SVM的分类质量恶化。 本发明的实施例涉及一种加权近端SVM（WPSVM）模型，其实现与传统SVM模型基本相同的精度，同时需要显着更少的计算时间。 根据本发明的实施例的加权近端SVM（WPSVM）模型可以包括每个训练误差的权重以及用于估计权重的方法，其自动地解决不平衡数据问题。 而且，不是通过KKT（Karush-Kuhn-Tucker）条件和Sherman-Morrison-Woodbury公式来解决优化问题，而是本发明的实施例使用迭代算法来解决无约束优化问题，这使得WPSVM适合于相对分类 高维数据。

公开(公告)号：US20070239553A1

公开(公告)日：2007-10-11

申请号：US11377130

申请日：2006-03-16

申请人： Chenxi Lin ,  Gui-Rong Xue ,  Hua-Jun Zeng ,  Zheng Chen ,  Benyu Zhang ,  Jian Wang

发明人： Chenxi Lin ,  Gui-Rong Xue ,  Hua-Jun Zeng ,  Zheng Chen ,  Benyu Zhang ,  Jian Wang

IPC分类号： G06Q30/00

CPC分类号： G06Q30/0623 ,  G06F16/9535 ,  G06Q30/0242 ,  G06Q30/0274

摘要： In an embodiment, a method of predicting an active user's rating for an item is disclosed. A database of users may be sorted into clusters. The data associated with the users in each cluster may be smoothed to filling in ratings for items that the users have not personally rated. An active user may then be compared to a set of users, where the set may be all or some portion of the database, to determine the K users that are most similar to the active user. The ratings of the K users regarding the item may be used to predict the active user's rating for the item. In an embodiment, the rating of each of the K users is assigned a confidence value associated with whether the user personally rated the item or if the rating was generated by the data smoothing process.

摘要翻译： 在一个实施例中，公开了一种用于预测项目的活跃用户评级的方法。 可以将用户的数据库分类为群集。 可以平滑与每个群集中的用户相关联的数据，以填充用户未被评估的项目的评级。 然后可以将活动用户与一组用户进行比较，其中该集合可以是数据库的全部或部分，以确定与活动用户最相似的K个用户。 关于该项目的K个用户的评级可以用于预测该项目的活动用户的评级。 在一个实施例中，每个K个用户的评级被分配与用户个人评价该项目相关联的置信度值，或者如果该评级是由数据平滑处理产生的。