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1. 发明申请

US20100145956A1 PSEUDO-ANCHOR TEXT EXTRACTION 有权
标题翻译： PSEUDO-ANCHOR文本提取
公开(公告)号：US20100145956A1
公开(公告)日：2010-06-10
申请号：US12697056
申请日：2010-01-29
申请人： Shuming Shi , Zaiqing Nie , Ji-Rong Wen , Mingjie Zhu , Fei Xing
发明人： Shuming Shi , Zaiqing Nie , Ji-Rong Wen , Mingjie Zhu , Fei Xing
IPC分类号： G06F17/30
CPC分类号： G06F17/30616 , G06F17/30864 , Y10S707/99932
摘要： A search method uses pseudo-anchor text associated with search objects to improve search performance. The pseudo-anchor text may be extracted in combination with an identifier of the search objects (such as a pseudo-URL) from a digital corpus such as a collection of documents. Pseudo-anchor texts for each object are preferably extracted from candidate anchor blocks using a machine learning based approach. The pseudo-anchor texts are made available for searching and used to help rank the objects in a search result to improve search performance. The method may be used in vertical search of objects such as published articles, products and images that lack explicit URLs and anchor text information.
摘要翻译：搜索方法使用与搜索对象相关联的伪锚文本来改善搜索性能。伪锚文本可以与来自诸如文档集合的数字语料库的搜索对象（诸如伪URL）的标识符组合提取。优选地，使用基于机器学习的方法从候选锚块中提取每个对象的伪锚文本。伪锚文本可用于搜索，并用于帮助对搜索结果中的对象进行排名以提高搜索性能。该方法可以用于垂直搜索诸如已发表的文章，产品和缺乏明确的URL和锚文本信息的图像的对象。

2. 发明申请

US20080215563A1 Pseudo-Anchor Text Extraction for Vertical Search 失效
标题翻译：用于垂直搜索的伪锚文本提取
公开(公告)号：US20080215563A1
公开(公告)日：2008-09-04
申请号：US11681682
申请日：2007-03-02
申请人： Shuming Shi , Zaiqing Nie , Ji-Rong Wen , Mingjie Zhu , Fei Xing
发明人： Shuming Shi , Zaiqing Nie , Ji-Rong Wen , Mingjie Zhu , Fei Xing
IPC分类号： G06F17/30
CPC分类号： G06F17/30616 , G06F17/30864 , Y10S707/99932
摘要： A search method uses pseudo-anchor text associated with search objects to improve search performance. The pseudo-anchor text may be extracted in combination with an identifier of the search objects (such as a pseudo-URL) from a digital corpus such as a collection of documents. Pseudo-anchor texts for each object are preferably extracted from candidate anchor blocks using a machine learning based approach. The pseudo-anchor texts are made available for searching and used to help ranking the objects in a search result to improve search performance. Method may be used in vertical search of objects such as published articles, products and images that lack explicit URL and anchor text information.
摘要翻译：搜索方法使用与搜索对象相关联的伪锚文本来改善搜索性能。伪锚文本可以与来自诸如文档集合的数字语料库的搜索对象（诸如伪URL）的标识符组合提取。优选地，使用基于机器学习的方法从候选锚块中提取每个对象的伪锚文本。伪锚文本可用于搜索，并用于帮助对搜索结果中的对象进行排名以提高搜索性能。方法可用于垂直搜索诸如已发表的文章，产品和图像之类的对象，缺少明确的URL和锚文本信息。

3. 发明授权

US08073838B2 Pseudo-anchor text extraction 有权
标题翻译：伪锚文本提取
公开(公告)号：US08073838B2
公开(公告)日：2011-12-06
申请号：US12697056
申请日：2010-01-29
申请人： Shuming Shi , Ji-Rong Wen , Mingjie Zhu , Fei Xing , Zaiqing Nie
发明人： Shuming Shi , Ji-Rong Wen , Mingjie Zhu , Fei Xing , Zaiqing Nie
IPC分类号： G06F17/30
CPC分类号： G06F17/30616 , G06F17/30864 , Y10S707/99932
摘要： A search method uses pseudo-anchor text associated with search objects to improve search performance. The pseudo-anchor text may be extracted in combination with an identifier of the search objects (such as a pseudo-URL) from a digital corpus such as a collection of documents. Pseudo-anchor texts for each object are preferably extracted from candidate anchor blocks using a machine learning based approach. The pseudo-anchor texts are made available for searching and used to help rank the objects in a search result to improve search performance. The method may be used in vertical search of objects such as published articles, products and images that lack explicit URLs and anchor text information.
摘要翻译：搜索方法使用与搜索对象相关联的伪锚文本来改善搜索性能。伪锚文本可以与来自诸如文档集合的数字语料库的搜索对象（诸如伪URL）的标识符组合提取。优选地，使用基于机器学习的方法从候选锚块中提取每个对象的伪锚文本。伪锚文本可用于搜索，并用于帮助对搜索结果中的对象进行排名以提高搜索性能。该方法可以用于垂直搜索诸如已发表的文章，产品和缺乏明确的URL和锚文本信息的图像的对象。

4. 发明授权

US07657507B2 Pseudo-anchor text extraction for vertical search 失效
标题翻译：用于垂直搜索的伪锚文本提取
公开(公告)号：US07657507B2
公开(公告)日：2010-02-02
申请号：US11681682
申请日：2007-03-02
申请人： Shuming Shi , Zaiqing Nie , Ji-Rong Wen , Mingjie Zhu , Fei Xing
发明人： Shuming Shi , Zaiqing Nie , Ji-Rong Wen , Mingjie Zhu , Fei Xing
IPC分类号： G06F17/30
CPC分类号： G06F17/30616 , G06F17/30864 , Y10S707/99932
摘要： A search method uses pseudo-anchor text associated with search objects to improve search performance. The pseudo-anchor text may be extracted in combination with an identifier of the search objects (such as a pseudo-URL) from a digital corpus such as a collection of documents. Pseudo-anchor texts for each object are preferably extracted from candidate anchor blocks using a machine learning based approach. The pseudo-anchor texts are made available for searching and used to help ranking the objects in a search result to improve search performance. Method may be used in vertical search of objects such as published articles, products and images that lack explicit URL and anchor text information.
摘要翻译：搜索方法使用与搜索对象相关联的伪锚文本来改善搜索性能。伪锚文本可以与来自诸如文档集合的数字语料库的搜索对象（诸如伪URL）的标识符组合提取。优选地，使用基于机器学习的方法从候选锚块中提取每个对象的伪锚文本。伪锚文本可用于搜索，并用于帮助对搜索结果中的对象进行排名以提高搜索性能。方法可用于垂直搜索诸如已发表的文章，产品和图像之类的对象，缺少明确的URL和锚文本信息。

5. 发明申请

US20080027910A1 WEB OBJECT RETRIEVAL BASED ON A LANGUAGE MODEL 失效
标题翻译：基于语言模型的WEB对象检索
公开(公告)号：US20080027910A1
公开(公告)日：2008-01-31
申请号：US11459857
申请日：2006-07-25
申请人： Ji-Rong Wen , Shuming Shi , Wei-Ying Ma , Yunxiao Ma , Zaiqing Nie
发明人： Ji-Rong Wen , Shuming Shi , Wei-Ying Ma , Yunxiao Ma , Zaiqing Nie
IPC分类号： G06F17/30
CPC分类号： G06F17/30687 , G06F17/30864 , G06F17/30896 , Y10S707/99936
摘要： A method and system is provided for determining relevance of an object to a term based on a language model. The relevance system provides records extracted from web pages that relate to the object. To determine the relevance of the object to a term, the relevance system first determines, for each record of the object, a probability of generating that term using a language model of the record of that object. The relevance system then calculates the relevance of the object to the term by combining the probabilities. The relevance system may also weight the probabilities based on the accuracy or reliability of the extracted information for each data source.
摘要翻译：提供了一种基于语言模型来确定对象与术语的相关性的方法和系统。相关系统提供从与该对象相关的网页提取的记录。为了确定对象与术语的相关性，相关系统首先确定对象的每个记录，使用该对象的记录的语言模型生成该术语的概率。相关系统然后通过组合概率来计算对象与该术语的相关性。相关系统还可以基于每个数据源提取的信息的准确性或可靠性对概率进行加权。

6. 发明授权

US08001130B2 Web object retrieval based on a language model 失效
标题翻译：基于语言模型的Web对象检索
公开(公告)号：US08001130B2
公开(公告)日：2011-08-16
申请号：US11459857
申请日：2006-07-25
申请人： Ji-Rong Wen , Shuming Shi , Wei-Ying Ma , Yunxiao Ma , Zaiqing Nie
发明人： Ji-Rong Wen , Shuming Shi , Wei-Ying Ma , Yunxiao Ma , Zaiqing Nie
IPC分类号： G06F17/30
CPC分类号： G06F17/30687 , G06F17/30864 , G06F17/30896 , Y10S707/99936
摘要： A method and system is provided for determining relevance of an object to a term based on a language model. The relevance system provides records extracted from web pages that relate to the object. To determine the relevance of the object to a term, the relevance system first determines, for each record of the object, a probability of generating that term using a language model of the record of that object. The relevance system then calculates the relevance of the object to the term by combining the probabilities. The relevance system may also weight the probabilities based on the accuracy or reliability of the extracted information for each data source.
摘要翻译：提供了一种基于语言模型来确定对象与术语的相关性的方法和系统。相关系统提供从与该对象相关的网页提取的记录。为了确定对象与术语的相关性，相关系统首先确定对象的每个记录，使用该对象的记录的语言模型生成该术语的概率。相关系统然后通过组合概率来计算对象与该术语的相关性。相关系统还可以基于每个数据源提取的信息的准确性或可靠性对概率进行加权。

7. 发明申请

US20110264658A1 WEB OBJECT RETRIEVAL BASED ON A LANGUAGE MODEL 审中-公开
标题翻译：基于语言模型的WEB对象检索
公开(公告)号：US20110264658A1
公开(公告)日：2011-10-27
申请号：US13175796
申请日：2011-07-01
申请人： Ji-Rong Wen , Shuming Shi , Wei-Ying Ma , Yunxiao Ma , Zaiqing Nie
发明人： Ji-Rong Wen , Shuming Shi , Wei-Ying Ma , Yunxiao Ma , Zaiqing Nie
IPC分类号： G06F17/30
CPC分类号： G06F16/3346 , G06F16/951 , G06F16/986 , Y10S707/99936
摘要： A method and system is provided for determining relevance of an object to a term based on a language model. The relevance system provides records extracted from web pages that relate to the object. To determine the relevance of the object to a term, the relevance system first determines, for each record of the object, a probability of generating that term using a language model of the record of that object. The relevance system then calculates the relevance of the object to the term by combining the probabilities. The relevance system may also weight the probabilities based on the accuracy or reliability of the extracted information for each data source.
摘要翻译：提供了一种基于语言模型来确定对象与术语的相关性的方法和系统。相关系统提供从与该对象相关的网页提取的记录。为了确定对象与术语的相关性，相关系统首先确定对象的每个记录，使用该对象的记录的语言模型生成该术语的概率。相关系统然后通过组合概率来计算对象与该术语的相关性。相关系统还可以基于每个数据源提取的信息的准确性或可靠性对概率进行加权。

8. 发明授权

US08538898B2 Interactive framework for name disambiguation 有权
标题翻译：互动框架的名称消歧
公开(公告)号：US08538898B2
公开(公告)日：2013-09-17
申请号：US13118404
申请日：2011-05-28
申请人： Zhengdong Lu , Zaiqing Nie , Gang Luo , Yong Cao , Ji-Rong Wen , Wei-Ying Ma
发明人： Zhengdong Lu , Zaiqing Nie , Gang Luo , Yong Cao , Ji-Rong Wen , Wei-Ying Ma
IPC分类号： G06N5/00
CPC分类号： G06N99/005 , G06F17/30616
摘要： A “Name Disambiguator” provides various techniques for implementing an interactive framework for resolving or disambiguating entity names (associated with objects such as publications) for entity searches where two or more same or similar names may refer to different entities. More specifically, the Name Disambiguator uses a combination of user input and automatic models to address the disambiguation problem. In various embodiments, the Name Disambiguator uses a two part process, including: 1) a global SVM trained from large sets of documents or objects in a simulated interactive mode, and 2) further personalization of local SVM models (associated with individual names or groups of names such as, for example, a group of coauthors) derived from the global SVM model. The result of this process is that large sets of documents or objects are rapidly and accurately condensed or clustered into ordered sets by that are organized by entity names.
摘要翻译： “名称歧义者”提供了各种技术，用于实现用于解析或消除实体名称（与诸如出版物的对象相关联）的交互式框架，用于实体搜索，其中两个或多个相同或相似的名称可以指代不同的实体。更具体地说，名称消歧器使用用户输入和自动模型的组合来解决消歧问题。在各种实施例中，名称消歧器使用两部分过程，包括：1）以模拟交互模式从大量文档或对象训练的全局SVM，以及2）本地SVM模型的进一步个性化（与个体名称或组相关联来自全球SVM模型的名称，例如一组合作者。这个过程的结果是，大量的文档或对象可以通过按实体名称组织的快速，准确的浓缩或聚类成有序集。

9. 发明授权

US07720830B2 Hierarchical conditional random fields for web extraction 失效
标题翻译： Web提取的分层条件随机字段
公开(公告)号：US07720830B2
公开(公告)日：2010-05-18
申请号：US11461400
申请日：2006-07-31
申请人： Ji-Rong Wen , Wei-Ying Ma , Zaiqing Nie , Jun Zhu
发明人： Ji-Rong Wen , Wei-Ying Ma , Zaiqing Nie , Jun Zhu
IPC分类号： G06F7/00 , G06F17/30 , G06F17/00 , G06F15/173
CPC分类号： G06F17/3089 , G06F17/30994
摘要： A method and system for labeling object information of an information page is provided. A labeling system identifies an object record of an information page based on the labeling of object elements within an object record and labels object elements based on the identification of an object record that contains the object elements. To identify the records and label the elements, the labeling system generates a hierarchical representation of blocks of an information page. The labeling system identifies records and elements within the records by propagating probability-related information of record labels and element labels through the hierarchy of the blocks. The labeling system generates a feature vector for each block to represent the block and calculates a probability of a label for a block being correct based on a score derived from the feature vectors associated with related blocks. The labeling system searches for the labeling of records and elements that has the highest probability of being correct.
摘要翻译：提供了一种用于标记信息页面的对象信息的方法和系统。标签系统基于对象记录中的对象元素的标签来识别信息页面的对象记录，并且基于包含对象元素的对象记录的标识来标记对象元素。为了识别记录并标记元素，标签系统生成信息页的块的分层表示。标签系统通过块的层次传播记录标签和元素标签的概率相关信息来识别记录中的记录和元素。标签系统为每个块生成特征向量以表示块，并且基于从与相关块相关联的特征向量导出的分数来计算块正确的标签的概率。标签系统搜索具有最高准确概率的记录和元素的标签。

10. 发明授权

US07529748B2 Information classification paradigm 有权
标题翻译：信息分类范式
公开(公告)号：US07529748B2
公开(公告)日：2009-05-05
申请号：US11276818
申请日：2006-03-15
申请人： Ji-Rong Wen , Yan-Feng Sun , Wei-Ying Ma , Zaiqing Nie , Renkuan Jiang
发明人： Ji-Rong Wen , Yan-Feng Sun , Wei-Ying Ma , Zaiqing Nie , Renkuan Jiang
IPC分类号： G06F17/30
CPC分类号： G06F17/30707 , Y10S707/99933 , Y10S707/99937
摘要： A mechanism to classify source documents into one of two categories, either likely to contain desired information or unlikely to contain desired information. Generally some form of rules based classification in conjunction with deeper analysis using advanced techniques on difficult cases is utilized. The rules based classification is generally good for eliminating cases from further consideration and for identifying documents of interest based on generally discernable relationships between data or based on the presence or absence of data. The deeper analysis is used to uncover more complex relationships between data that may identify documents of interest. Portions of the process may use the entire document while other portions of the process may use only a portion of the document.
摘要翻译：将源文档分类为两个类别之一的机制，可能包含所需信息或不太可能包含所需信息。通常使用某种形式的基于规则的分类，结合使用先进技术在困难案例上进行更深入的分析。基于规则的分类通常对于消除进一步考虑的情况以及基于数据之间的一般可辨别的关系或基于数据的存在或不存在来识别感兴趣的文档是有益的。更深入的分析用于发现可能识别感兴趣文档的数据之间更复杂的关系。过程的一部分可以使用整个文档，而进程的其他部分可以仅使用文档的一部分。

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