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1. 发明申请

US20120203777A1 Finding and Disambiguating References to Entities on Web Pages 有权
标题翻译：查找和消除对网页上实体的引用
公开(公告)号：US20120203777A1
公开(公告)日：2012-08-09
申请号：US13364244
申请日：2012-02-01
申请人： Leonardo A. Laroco, JR. , Nikola Jevtic , Nikolai V. Yakovenko , Jeffrey Reynar
发明人： Leonardo A. Laroco, JR. , Nikola Jevtic , Nikolai V. Yakovenko , Jeffrey Reynar
IPC分类号： G06F17/30
CPC分类号： G06F17/30011 , G06F17/30876 , G06N5/04 , G06N99/005
摘要： A system and method for disambiguating references to entities in a document. In one embodiment, an iterative process is used to disambiguate references to entities in documents. An initial model is used to identify documents referring to an entity based on features contained in those documents. The occurrence of various features in these documents is measured. From the number occurrences of features in these documents, a second model is constructed. The second model is used to identify documents referring to the entity based on features contained in the documents. The process can be repeated, iteratively identifying documents referring to the entity and improving subsequent models based on those identifications. Additional features of the entity can be extracted from documents identified as referring to the entity.
摘要翻译：一种用于消除文档中对实体的引用的系统和方法。在一个实施例中，迭代过程用于消除对文档中对实体的引用。初始模型用于根据这些文档中包含的特征来识别引用实体的文档。测量这些文件中各种特征的出现情况。从这些文件中的特征数出现，构建第二个模型。第二个模型用于根据文档中包含的功能来识别引用该实体的文档。该过程可以重复，迭代地识别参考实体的文档，并且基于这些标识来改进随后的模型。实体的附加特征可以从标识为引用实体的文档中提取出来。

2. 发明授权

US08751498B2 Finding and disambiguating references to entities on web pages 有权
标题翻译：查找和消除对网页上实体的引用
公开(公告)号：US08751498B2
公开(公告)日：2014-06-10
申请号：US13364244
申请日：2012-02-01
申请人： Leonardo A. Laroco, Jr. , Nikola Jevtic , Nikolai V. Yakovenko , Jeffrey Reynar
发明人： Leonardo A. Laroco, Jr. , Nikola Jevtic , Nikolai V. Yakovenko , Jeffrey Reynar
IPC分类号： G06F17/30
CPC分类号： G06F17/30011 , G06F17/30876 , G06N5/04 , G06N99/005
摘要： A system and method for disambiguating references to entities in a document. In one embodiment, an iterative process is used to disambiguate references to entities in documents. An initial model is used to identify documents referring to an entity based on features contained in those documents. The occurrence of various features in these documents is measured. From the number occurrences of features in these documents, a second model is constructed. The second model is used to identify documents referring to the entity based on features contained in the documents. The process can be repeated, iteratively identifying documents referring to the entity and improving subsequent models based on those identifications. Additional features of the entity can be extracted from documents identified as referring to the entity.
摘要翻译：一种用于消除文档中对实体的引用的系统和方法。在一个实施例中，迭代过程用于消除对文档中对实体的引用。初始模型用于根据这些文档中包含的特征来识别引用实体的文档。测量这些文件中各种特征的出现情况。从这些文件中的特征数出现，构建第二个模型。第二个模型用于根据文档中包含的功能来识别引用该实体的文档。该过程可以重复，迭代地识别参考实体的文档，并且基于这些标识来改进随后的模型。实体的附加特征可以从标识为引用实体的文档中提取出来。

3. 发明授权

US08122026B1 Finding and disambiguating references to entities on web pages 有权
标题翻译：查找和消除对网页上实体的引用
公开(公告)号：US08122026B1
公开(公告)日：2012-02-21
申请号：US11551657
申请日：2006-10-20
申请人： Leonardo A. Laroco, Jr. , Nikola Jevtic , Nikolai V. Yakovenko , Jeffrey Reynar
发明人： Leonardo A. Laroco, Jr. , Nikola Jevtic , Nikolai V. Yakovenko , Jeffrey Reynar
IPC分类号： G06F17/30
CPC分类号： G06F17/30011 , G06F17/30876 , G06N5/04 , G06N99/005
摘要： A system and method for disambiguating references to entities in a document. In one embodiment, an iterative process is used to disambiguate references to entities in documents. An initial model is used to identify documents referring to an entity based on features contained in those documents. The occurrence of various features in these documents is measured. From the number occurrences of features in these documents, a second model is constructed. The second model is used to identify documents referring to the entity based on features contained in the documents. The process can be repeated, iteratively identifying documents referring to the entity and improving subsequent models based on those identifications. Additional features of the entity can be extracted from documents identified as referring to the entity.
摘要翻译：一种用于消除对文档中对实体的引用的系统和方法。在一个实施例中，迭代过程用于消除对文档中对实体的引用。初始模型用于根据这些文档中包含的特征来识别引用实体的文档。测量这些文件中各种特征的出现情况。从这些文件中的特征数出现，构建第二个模型。第二个模型用于根据文档中包含的功能来识别引用该实体的文档。该过程可以重复，迭代地识别参考实体的文档，并且基于这些标识来改进随后的模型。实体的附加特征可以从标识为引用实体的文档中提取出来。

4. 发明申请

US20100281034A1 Query-Independent Entity Importance in Books 有权
标题翻译：查询独立实体在图书中的重要性
公开(公告)号：US20100281034A1
公开(公告)日：2010-11-04
申请号：US12837206
申请日：2010-07-15
申请人： David Petrou , Chiu-Ki Chan , Daniel Loreto , Jeffrey C. Reynar , Nikola Jevtic
发明人： David Petrou , Chiu-Ki Chan , Daniel Loreto , Jeffrey C. Reynar , Nikola Jevtic
IPC分类号： G06F17/30
CPC分类号： G06F17/30864 , G06F17/30657
摘要： A corpus contains information including text from books and metadata about the books. The book texts mention entities of various types, such as location, date, event, and person entities. An entity importance engine analyzes the information in the corpus to identify the entities mentioned therein, and ranks the entities using query-independent importance scores. The importance scores can be based in part on the contexts in which the entities are mentioned by the books. A presentation engine enables searching of the corpus to identify books satisfying a search query. The presentation engine presents information about a designated book. Entities mentioned in the book are presented in a style selected to enhance comprehension and utility. For example, location entities can be presented on a map with markers showing the locations of the entities. The number of entities presented are limited and ordered based on the query-independent importance scores.
摘要翻译：语料库包含有书籍的文字和有关书籍的元数据的信息。书本提到各种类型的实体，如位置，日期，事件和个人实体。实体重要性引擎分析语料库中的信息以识别其中提到的实体，并且使用与查询无关的重要性得分对实体进行排序。重要性分数可以部分地基于实体被书籍提及的背景。演示文稿引擎可以搜索语料库来识别满足搜索查询的书籍。演示文稿引擎提供有关指定书籍的信息。本书中提到的实体以选择加强理解和实用性的风格呈现。例如，位置实体可以在具有显示实体的位置的标记的地图上呈现。所提出的实体数量是有限的，并且基于与查询无关的重要性分数进行排序。

5. 发明授权

US07783644B1 Query-independent entity importance in books 有权
标题翻译：书籍中与查询无关的实体重要性
公开(公告)号：US07783644B1
公开(公告)日：2010-08-24
申请号：US11610446
申请日：2006-12-13
申请人： David Petrou , Chiu-Ki Chan , Daniel Loreto , Jeffrey C. Reynar , Nikola Jevtic
发明人： David Petrou , Chiu-Ki Chan , Daniel Loreto , Jeffrey C. Reynar , Nikola Jevtic
IPC分类号： G06F7/08 , G06F17/30
CPC分类号： G06F17/30864 , G06F17/30657
摘要： A corpus contains information including text from books and metadata about the books. The book texts mention entities of various types, such as location, date, event, and person entities. An entity importance engine analyzes the information in the corpus to identify the entities mentioned therein, and ranks the entities using query-independent importance scores. The importance scores can be based in part on the contexts in which the entities are mentioned by the books. A presentation engine enables searching of the corpus to identify books satisfying a search query. The presentation engine presents information about a designated book. Entities mentioned in the book are presented in a style selected to enhance comprehension and utility. For example, location entities can be presented on a map with markers showing the locations of the entities. The number of entities presented are limited and ordered based on the query-independent importance scores.
摘要翻译：语料库包含有书籍的文字和有关书籍的元数据的信息。书本提到各种类型的实体，如位置，日期，事件和个人实体。实体重要性引擎分析语料库中的信息以识别其中提到的实体，并且使用与查询无关的重要性得分对实体进行排序。重要性分数可以部分地基于实体被书籍提及的背景。演示文稿引擎可以搜索语料库来识别满足搜索查询的书籍。演示文稿引擎提供有关指定书籍的信息。本书中提到的实体以选择加强理解和实用性的风格呈现。例如，位置实体可以在具有显示实体的位置的标记的地图上呈现。所提出的实体数量是有限的，并且基于与查询无关的重要性分数进行排序。

6. 发明授权

US07958128B2 Query-independent entity importance in books 有权
标题翻译：书籍中与查询无关的实体重要性
公开(公告)号：US07958128B2
公开(公告)日：2011-06-07
申请号：US12837206
申请日：2010-07-15
申请人： David Petrou , Chiu-Ki Chan , Daniel Loreto , Jeffrey C. Reynar , Nikola Jevtic
发明人： David Petrou , Chiu-Ki Chan , Daniel Loreto , Jeffrey C. Reynar , Nikola Jevtic
IPC分类号： G06F17/30
CPC分类号： G06F17/30864 , G06F17/30657
摘要： A corpus contains information including text from books and metadata about the books. The book texts mention entities of various types, such as location, date, event, and person entities. An entity importance engine analyzes the information in the corpus to identify the entities mentioned therein, and ranks the entities using query-independent importance scores. The importance scores can be based in part on the contexts in which the entities are mentioned by the books. A presentation engine enables searching of the corpus to identify books satisfying a search query. The presentation engine presents information about a designated book. Entities mentioned in the book are presented in a style selected to enhance comprehension and utility. For example, location entities can be presented on a map with markers showing the locations of the entities. The number of entities presented are limited and ordered based on the query-independent importance scores.
摘要翻译：语料库包含有书籍的文字和有关书籍的元数据的信息。书本提到各种类型的实体，如位置，日期，事件和个人实体。实体重要性引擎分析语料库中的信息以识别其中提到的实体，并且使用与查询无关的重要性得分对实体进行排序。重要性分数可以部分地基于实体被书籍提及的背景。演示文稿引擎可以搜索语料库来识别满足搜索查询的书籍。演示文稿引擎提供有关指定书籍的信息。本书中提到的实体以选择加强理解和实用性的风格呈现。例如，位置实体可以在具有显示实体的位置的标记的地图上呈现。所提出的实体数量是有限的，并且基于与查询无关的重要性分数进行排序。

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