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1. 发明授权

US07739261B2 Identification of topics for online discussions based on language patterns 有权
标题翻译：基于语言模式识别在线讨论的主题
公开(公告)号：US07739261B2
公开(公告)日：2010-06-15
申请号：US11763282
申请日：2007-06-14
申请人： Hua-Jun Zeng , Hua Li , Jian Hu , Zheng Chen , Duo Zhang , Jian Wang
发明人： Hua-Jun Zeng , Hua Li , Jian Hu , Zheng Chen , Duo Zhang , Jian Wang
IPC分类号： G06F17/30
CPC分类号： G06F17/30731 , G06Q30/02
摘要： A topic identification system identifies topics of online discussions by iteratively identifying topic words or keywords of the online discussions and identifying language patterns associated with those keywords. The topic identification system starts out with an initial set of keywords and identifies language patterns that each include a keyword. The topic identification system then uses the identified language patterns to identify additional keywords of the online discussion that match the patterns. The topic identification system then again identifies language patterns using the keywords including the newly identified keywords. The topic identification system may repeat the process of identifying language patterns and keywords until a termination criterion is satisfied.
摘要翻译：主题识别系统通过迭代地识别在线讨论的主题或关键字并识别与这些关键字相关联的语言模式来识别在线讨论的主题。主题识别系统以一组初始关键字开始，并识别每个关键字的语言模式。然后，主题识别系统使用所识别的语言模式来识别与模式匹配的在线讨论的附加关键字。然后，主题识别系统再次使用包括新确定的关键字的关键字来识别语言模式。主题识别系统可以重复识别语言模式和关键字的过程，直到满足终止标准。

2. 发明申请

US20080313180A1 IDENTIFICATION OF TOPICS FOR ONLINE DISCUSSIONS BASED ON LANGUAGE PATTERNS 有权
标题翻译：基于语言模式的在线讨论主题的识别
公开(公告)号：US20080313180A1
公开(公告)日：2008-12-18
申请号：US11763282
申请日：2007-06-14
申请人： Hua-Jun Zeng , Hua Li , Jian Hu , Zheng Chen , Duo Zhang , Jian Wang
发明人： Hua-Jun Zeng , Hua Li , Jian Hu , Zheng Chen , Duo Zhang , Jian Wang
IPC分类号： G06F17/30
CPC分类号： G06F17/30731 , G06Q30/02
摘要： A topic identification system identifies topics of online discussions by iteratively identifying topic words or keywords of the online discussions and identifying language patterns associated with those keywords. The topic identification system starts out with an initial set of keywords and identifies language patterns that each include a keyword. The topic identification system then uses the identified language patterns to identify additional keywords of the online discussion that match the patterns. The topic identification system then again identifies language patterns using the keywords including the newly identified keywords. The topic identification system may repeat the process of identifying language patterns and keywords until a termination criterion is satisfied.
摘要翻译：主题识别系统通过迭代地识别在线讨论的主题或关键字并识别与这些关键字相关联的语言模式来识别在线讨论的主题。主题识别系统以一组初始关键字开始，并识别每个关键字的语言模式。然后，主题识别系统使用所识别的语言模式来识别与模式匹配的在线讨论的附加关键字。然后，主题识别系统再次使用包括新确定的关键字的关键字来识别语言模式。主题识别系统可以重复识别语言模式和关键字的过程，直到满足终止标准。

3. 发明申请

US20080300971A1 ADVERTISEMENT APPROVAL BASED ON TRAINING DATA 审中-公开
标题翻译：基于培训数据的广告批准
公开(公告)号：US20080300971A1
公开(公告)日：2008-12-04
申请号：US11755523
申请日：2007-05-30
申请人： Hua-Jun Zeng , Hua Li , Jian Hu , Zheng Chen , Jian Wang
发明人： Hua-Jun Zeng , Hua Li , Jian Hu , Zheng Chen , Jian Wang
IPC分类号： G06Q30/00
CPC分类号： G06Q30/02 , G06Q30/0242 , G06Q30/0254 , G06Q30/0256 , G06Q30/0263
摘要： A system for determining whether to approve a target document (e.g., advertisement) is provided. The system trains a classifier using tuples of words from appropriate documents and tuples of words from inappropriate documents. To approve a target document, the system identifies tuples of words of the target document. The system then applies the classifier to the identified tuples to classify the document as being appropriate or inappropriate. If the document is classified as appropriate, the system automatically approves the document.
摘要翻译：提供用于确定是否批准目标文档（例如，广告）的系统。系统使用适当文件的单词组和不适当文件的单词元组来训练分类器。要批准目标文档，系统会标识目标文档的单词元组。然后，系统将分类器应用于所识别的元组，以将文档分类为合适或不合适。如果文档被分类为适当的，系统将自动批准文档。

4. 发明申请

US20080301117A1 KEYWORD USAGE SCORE BASED ON FREQUENCY IMPULSE AND FREQUENCY WEIGHT 失效
标题翻译：基于频率和频率的关键字使用分数
公开(公告)号：US20080301117A1
公开(公告)日：2008-12-04
申请号：US11756740
申请日：2007-06-01
申请人： Hua-Jun Zeng , Hua Li , Jian Hu , Han Peng , Zheng Chen , Jian Wang
发明人： Hua-Jun Zeng , Hua Li , Jian Hu , Han Peng , Zheng Chen , Jian Wang
IPC分类号： G06F7/76 , G06F17/30
CPC分类号： G06F17/30864 , Y10S707/99935
摘要： A method and system for assessing keyword usage based on frequency of usage of the keywords during various periods is provided. A keyword usage measurement system is provided with the frequency of keywords during various periods. The measurement system then calculates a recent usage score for a keyword by combining a frequency impulse score for the keyword with a frequency weight for the keyword. The frequency impulse score for a keyword indicates whether a recent change in the frequency of the keyword has occurred. The frequency weight for a keyword indicates a recent measure of the frequency of the keyword.
摘要翻译：提供了一种基于各种期间关键词使用频率来评估关键字使用的方法和系统。关键字使用测量系统在不同时期提供关键字的频率。然后，测量系统通过将关键字的频率脉冲得分与该关键字的频率权重组合来计算关键字的最近使用分数。关键字的频率脉冲得分指示是否发生了关键字的频率的最近的改变。关键字的频率权重表示最近对关键字频率的度量。

5. 发明授权

US07644075B2 Keyword usage score based on frequency impulse and frequency weight 失效
标题翻译：基于频率冲击和频率权重的关键词使用得分
公开(公告)号：US07644075B2
公开(公告)日：2010-01-05
申请号：US11756740
申请日：2007-06-01
申请人： Hua-Jun Zeng , Hua Li , Jian Hu , Han Peng , Zheng Chen , Jian Wang
发明人： Hua-Jun Zeng , Hua Li , Jian Hu , Han Peng , Zheng Chen , Jian Wang
IPC分类号： G06F17/30
CPC分类号： G06F17/30864 , Y10S707/99935
摘要： A method and system for assessing keyword usage based on frequency of usage of the keywords during various periods is provided. A keyword usage measurement system is provided with the frequency of keywords during various periods. The measurement system then calculates a recent usage score for a keyword by combining a frequency impulse score for the keyword with a frequency weight for the keyword. The frequency impulse score for a keyword indicates whether a recent change in the frequency of the keyword has occurred. The frequency weight for a keyword indicates a recent measure of the frequency of the keyword.
摘要翻译：提供了一种基于各种期间关键词使用频率来评估关键字使用的方法和系统。关键字使用测量系统在不同时期提供关键字的频率。然后，测量系统通过将关键字的频率脉冲得分与该关键字的频率权重组合来计算关键字的最近使用分数。关键字的频率脉冲得分指示是否发生了关键字的频率的最近的改变。关键字的频率权重表示最近对关键字频率的度量。

6. 发明申请

US20080103886A1 DETERMINING RELEVANCE OF A TERM TO CONTENT USING A COMBINED MODEL 审中-公开
标题翻译：使用组合模型确定期限与内容的相关性
公开(公告)号：US20080103886A1
公开(公告)日：2008-05-01
申请号：US11553897
申请日：2006-10-27
申请人： Hua Li , Zheng Chen , Benyu Zhang , Hua-Jun Zeng , Jian Wang
发明人： Hua Li , Zheng Chen , Benyu Zhang , Hua-Jun Zeng , Jian Wang
IPC分类号： G06Q30/00
CPC分类号： G06Q30/02 , G06Q30/0275 , G06Q30/0277
摘要： A method and system for generating and using a combined model to identify whether a bid term is relevant to an advertisement is provided. A relevance system trains a combined model that includes an initial model and a decision tree model that are trained using features that represent relationships between bid terms and advertisements. The relevance system trains the initial model to map initial model features to a modeled relevance. The relevance system trains the decision tree model to map the decision tree features and the modeled relevance to a final relevance. The trained initial model and decision tree model represent the combined model. The relevance system then uses the combined model to determine the relevance of bid terms to advertisements.
摘要翻译：提供了一种用于生成和使用组合模型以识别出价项是否与广告相关的方法和系统。相关系统训练包括初始模型和决策树模型的组合模型，该模型使用表示投标条款和广告之间关系的特征来训练。相关系统训练初始模型以将初始模型特征映射到建模相关性。相关系统训练决策树模型，将决策树特征和建模相关性映射到最终相关性。训练初始模型和决策树模型代表组合模型。相关系统然后使用组合模型来确定投标条款与广告的相关性。

7. 发明授权

US08285745B2 User query mining for advertising matching 有权
标题翻译：用户查询挖掘广告匹配
公开(公告)号：US08285745B2
公开(公告)日：2012-10-09
申请号：US11849136
申请日：2007-08-31
申请人： Hua Li , HuaJun Zeng , Jian Hu , Zheng Chen , Jian Wang
发明人： Hua Li , HuaJun Zeng , Jian Hu , Zheng Chen , Jian Wang
IPC分类号： G06F17/30
CPC分类号： G06F17/30861 , G06F17/30672 , G06Q30/02
摘要： Systems and methods to determine relevant keywords from a user's search query sessions are disclosed. The described method includes identifying search session logs of a user, segmenting the search session logs into one or more search sessions. After the segmentation, the search sessions are analyzed to compose a list of semantically relevant keyword sets including at least a first keyword set and a second keyword set. The described method further includes determining a semantic relevance between the first and second keyword sets according to the frequency at which the first and second keyword sets are reported in the query results and displaying one or more semantically high relevant keyword sets after being filtered by a threshold.
摘要翻译：公开了从用户的搜索查询会话确定相关关键词的系统和方法。所描述的方法包括识别用户的搜索会话日志，将搜索会话日志分割成一个或多个搜索会话。在分割之后，分析搜索会话以构成包括至少第一关键词集合和第二关键字集合的语义相关关键字集合的列表。所描述的方法还包括根据在查询结果中报告第一和第二关键字集合的频率来确定第一和第二关键字集合之间的语义相关性，并且在被阈值过滤之后显示一个或多个语义上相关的关键字集合。

8. 发明申请

US20090063461A1 USER QUERY MINING FOR ADVERTISING MATCHING 有权
标题翻译：用户查询采购广告匹配
公开(公告)号：US20090063461A1
公开(公告)日：2009-03-05
申请号：US11849136
申请日：2007-08-31
申请人： Jian Wang , Hua Li , HuaJun Zeng , Jian Hu , Zheng Chen
发明人： Jian Wang , Hua Li , HuaJun Zeng , Jian Hu , Zheng Chen
IPC分类号： G06F7/06 , G06F17/30
CPC分类号： G06F17/30861 , G06F17/30672 , G06Q30/02
摘要： Systems and methods to determine relevant keywords from a user's search query sessions are disclosed. The described method includes identifying search session logs of a user, segmenting the search session logs into one or more search sessions. After the segmentation, the search sessions are analyzed to compose a list of semantically relevant keyword sets including at least a first keyword set and a second keyword set. The described method further includes determining a semantic relevance between the first and second keyword sets according to the frequency at which the first and second keyword sets are reported in the query results and displaying one or more semantically high relevant keyword sets after being filtered by a threshold.
摘要翻译：公开了从用户的搜索查询会话确定相关关键词的系统和方法。所描述的方法包括识别用户的搜索会话日志，将搜索会话日志分割成一个或多个搜索会话。在分割之后，分析搜索会话以构成包括至少第一关键词集合和第二关键字集合的语义相关关键字集合的列表。所描述的方法还包括根据在查询结果中报告第一和第二关键字集合的频率来确定第一和第二关键字集合之间的语义相关性，并且在被阈值过滤之后显示一个或多个语义上相关的关键字集合。

9. 发明申请

US20080208841A1 CLICK-THROUGH LOG MINING 有权
标题翻译：点击通过日志采矿
公开(公告)号：US20080208841A1
公开(公告)日：2008-08-28
申请号：US11870359
申请日：2007-10-10
申请人： Huajun Zeng , Jian Hu , Hua Li , Zheng Chen , Jian Wang
发明人： Huajun Zeng , Jian Hu , Hua Li , Zheng Chen , Jian Wang
IPC分类号： G06F17/30
CPC分类号： G06F17/30648 , G06F17/30672 , G06F17/30864
摘要： Click-through log mining is described. Raw search click-through log data is processed to generate ordered query keywords, utilizing an algorithm to expand user-submitted keywords to include high frequency user queries, managing the keywords for a keyword expansion file, analyzing the algorithm performance on a bidding criteria, and identifying related phrases with similar page-click behaviors for advertisements.
摘要翻译：描述了点击式日志挖掘。处理原始搜索点击后日志数据以生成有序查询关键字，利用算法来扩展用户提交的关键字以包括高频用户查询，管理关键字扩展文件的关键字，以出价标准分析算法性能;以及识别与广告相似的页面点击行为的相关短语。

10. 发明授权

US07707129B2 Text classification by weighted proximal support vector machine based on positive and negative sample sizes and weights 有权
标题翻译：基于正，负样本大小和权重的加权近端支持向量机进行文本分类
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。

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