公开(公告)号：US09116995B2

公开(公告)日：2015-08-25

申请号：US13434600

申请日：2012-03-29

申请人： Krzysztof Koperski ,  Satish Bhatti ,  Jisheng Liang ,  Adrian Klein

发明人： Krzysztof Koperski ,  Satish Bhatti ,  Jisheng Liang ,  Adrian Klein

IPC分类号： G06F7/00 ,  G06F17/30

CPC分类号： G06F17/30598 ,  G06F17/30663 ,  G06F17/30699 ,  G06F17/30705 ,  G06F17/30707 ,  G06F17/3071 ,  G06F17/30722 ,  G06F17/30867

摘要： Methods, systems, and techniques for cluster-based content recommendation are described. Some embodiments provide a content recommendation system (“CRS”) configured to recommend news stories about events or occurrences. In some embodiments, a news story about an event includes multiple related content items that each include an account of the event and that each reference one or more entities or categories that are represented by the CRS. In one embodiment, the CRS identifies news stories by generating clusters of related content items. Then, in response to a received query that indicates a keyterm, entity, or category, the CRS determines and provides indications of one or more news stories that are relevant to the received query. In some embodiments, at least some of these techniques are employed to implement a news story recommendation facility in an online news service.

摘要翻译： 描述了基于群集的内容推荐的方法，系统和技术。 一些实施例提供了被配置为推荐关于事件或事件的新闻故事的内容推荐系统（“CRS”）。 在一些实施例中，关于事件的新闻故事包括多个相关内容项，每个内容项包括事件的帐户，并且每个引用由CRS表示的一个或多个实体或类别。 在一个实施例中，CRS通过生成相关内容项目的集群来识别新闻故事。 然后，响应于接收到的指示关键字，实体或类别的查询，CRS确定并提供与所接收的查询相关的一个或多个新闻故事的指示。 在一些实施例中，使用这些技术中的至少一些来实现在线新闻服务中的新闻故事推荐设施。

公开(公告)号：US08645125B2

公开(公告)日：2014-02-04

申请号：US13075799

申请日：2011-03-30

申请人： Jisheng Liang ,  Navdeep Dhillon ,  Krzysztof Koperski

发明人： Jisheng Liang ,  Navdeep Dhillon ,  Krzysztof Koperski

IPC分类号： G06F17/27

CPC分类号： G06F17/278 ,  G06F17/2705 ,  G06F17/274 ,  G06F17/2775 ,  G06F17/28 ,  G06F17/30011 ,  G06F17/30684

摘要： Techniques for providing quotations obtained from text documents using natural language processing techniques are described. Some embodiments provide a content recommendation system (“CRS”) configured to provide quotations by extracting quotations from a corpus text documents, and providing access to the extracted quotations in response to search requests received from users. The CRS may extract quotations by using natural language processing-based techniques to identify one or more entities, such as people, places, objects, concepts, or the like, that are referenced by the extracted quotations. The CRS may then store the extracted quotations along with identified entities, such as quotation speakers and subjects, for later access via search requests.

摘要翻译： 描述使用自然语言处理技术从文本文档获得报价的技术。 一些实施例提供了一种内容推荐系统（“CRS”），其被配置为通过从语料库文本文档中提取报价来提供报价，并且响应于从用户接收的搜索请求提供对所提取的报价的访问。 CRS可以通过使用基于自然语言处理的技术来提取报价，以识别由提取的报价引用的一个或多个实体，例如人，地点，对象，概念等。 然后，CRS可以将所提取的报价与所识别的实体（例如引号说话者和主题）一起存储，以供稍后通过搜索请求访问。

公开(公告)号：US08594996B2

公开(公告)日：2013-11-26

申请号：US12288158

申请日：2008-10-15

申请人： Jisheng Liang ,  Krzysztof Koperski ,  Navdeep S. Dhillon ,  Carsten Tusk ,  Satish Bhatti

发明人： Jisheng Liang ,  Krzysztof Koperski ,  Navdeep S. Dhillon ,  Carsten Tusk ,  Satish Bhatti

IPC分类号： G06F17/27

CPC分类号： G06F17/21 ,  G06F17/278

摘要： Methods and systems for entity recognition and disambiguation using natural language processing techniques are provided. Example embodiments provide an entity recognition and disambiguation system (ERDS) and process that, based upon input of a text segment, automatically determines which entities are being referred to by the text using both natural language processing techniques and analysis of information gleaned from contextual data in the surrounding text. In at least some embodiments, supplemental or related information that can be used to assist in the recognition and/or disambiguation process can be retrieved from knowledge repositories such as an ontology knowledge base. In one embodiment, the ERDS comprises a linguistic analysis engine, a knowledge analysis engine, and a disambiguation engine that cooperate to identify candidate entities from a knowledge repository and determine which of the candidates best matches the one or more detected entities in a text segment using context information.

公开(公告)号：US20110282888A1

公开(公告)日：2011-11-17

申请号：US13038192

申请日：2011-03-01

申请人： Krzysztof Koperski ,  Jisheng Liang ,  Neil Roseman

发明人： Krzysztof Koperski ,  Jisheng Liang ,  Neil Roseman

IPC分类号： G06F17/30

CPC分类号： G06F17/30864 ,  G06F17/30867

摘要： Techniques for content recommendation are described. Some embodiments provide a content recommendation system (“CRS”) configured to recommend content items that are related to a collection of entities. A content item may be considered related to a collection of entities based on various factors, including whether and how often the article references or otherwise covers the entities of the collection, the size of the article, other entities that are covered by the article but that are not in the collection, article recency, or article credibility. Recommending content items may also or instead include determining entities that are related to a collection. An entity can be considered related to a collection based on various factors, such as whether the entity is of the same or similar type to entities of the collection, or whether the entity appears in some article in a relationship with one or more entities of the collection.

摘要翻译： 描述内容推荐的技术。 一些实施例提供了被配置为推荐与实体集合相关的内容项的内容推荐系统（“CRS”）。 内容项目可以被认为与基于各种因素的实体集合相关，包括文章引用或多次引用或以其他方式涵盖集合的实体，文章的大小，文章涵盖的其他实体，但是 不在收藏，文章新近或文章的可信度。 推荐内容项还可以或者替代地包括确定与集合相关的实体。 可以将实体视为基于各种因素与集合相关的实体，例如该实体与集合的实体是相同或相似的类型，或者该实体是否出现在与一个或多个实体的关系中的一些文章中 采集。

公开(公告)号：US20090144609A1

公开(公告)日：2009-06-04

申请号：US12288158

申请日：2008-10-15

申请人： Jisheng Liang ,  Krzysztof Koperski ,  Navdeep S. Dhillon ,  Carsten Tusk ,  Satish Bhatti

发明人： Jisheng Liang ,  Krzysztof Koperski ,  Navdeep S. Dhillon ,  Carsten Tusk ,  Satish Bhatti

IPC分类号： G06F7/06 ,  G06F17/30 ,  G06F17/00 ,  G06F3/048

CPC分类号： G06F17/21 ,  G06F17/278

摘要： Methods and systems for entity recognition and disambiguation using natural language processing techniques are provided. Example embodiments provide an entity recognition and disambiguation system (ERDS) and process that, based upon input of a text segment, automatically determines which entities are being referred to by the text using both natural language processing techniques and analysis of information gleaned from contextual data in the surrounding text. In at least some embodiments, supplemental or related information that can be used to assist in the recognition and/or disambiguation process can be retrieved from knowledge repositories such as an ontology knowledge base. In one embodiment, the ERDS comprises a linguistic analysis engine, a knowledge analysis engine, and a disambiguation engine that cooperate to identify candidate entities from a knowledge repository and determine which of the candidates best matches the one or more detected entities in a text segment using context information.

摘要翻译： 提供了使用自然语言处理技术进行实体识别和消歧的方法和系统。 示例性实施例提供了一种实体识别和消歧系统（ERDS）和过程，其基于文本段的输入，使用自然语言处理技术自动确定文本正在引用哪些实体以及从上下文数据中收集的信息的分析 周围的文字。 在至少一些实施例中，可以用于帮助识别和/或消歧过程的补充或相关信息可以从诸如本体知识库的知识库中检索。 在一个实施例中，ERDS包括语言分析引擎，知识分析引擎和消歧引擎，其协作以从知识库识别候选实体，并且使用以下方式确定哪个候选最符合文本段中的一个或多个检测到的实体 上下文信息。