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    • 12. 发明申请
    • ESTABLISHING
    • 建立“是一个关于TAXONOMY的关系”
    • US20140095411A1
    • 2014-04-03
    • US13630369
    • 2012-09-28
    • Digvijay Singh LambaOmkar Deshpande
    • Digvijay Singh LambaOmkar Deshpande
    • G06F15/18
    • G06F17/2785G06F16/332
    • Disclosed are methods for returning to a user an answer to the question “what is .” Concepts and classes to which the concepts belong are determined from a corpus, such as taxonomy. The concepts are mapped to categories according to the structure of the taxonomy. Homonyms for words are collected and scored according to likeliness of use. Concept vectors are assembled for the identified concepts based on articles in the corpus and social media usage. Words are evaluated for generic-ness and a generic score is associated therewith. In responding to a query, the generic-ness of the terms of the query is evaluated and additional context solicited if the terms are generic. Candidate homonym concepts for a string in the query are selected according to context vectors for the homonym concepts. One or more homonym concepts are selected and the one or more categories corresponding to these concepts are returned.
    • 公开的方法是向用户返回“什么是”的问题的答案。概念属于的概念和类是从语料库(如分类法)确定的。 概念根据分类结构映射到类别。 词的同义词根据使用的可能性进行收集和评分。 基于语料库和社交媒体使用中的文章,针对识别的概念组合概念向量。 对于通用性进行评估,并且通用分数与之相关联。 在响应查询时,如果术语是通用的,则对查询的条款的通用性进行评估,并附加附加内容。 根据和声概念的上下文向量选择查询中的字符串的候选和声概念。 选择一个或多个同音符概念,并且返回与这些概念对应的一个或多个类别。
    • 13. 发明申请
    • ESTABLISHING
    • 建立“是一个关于TAXONOMY的关系”
    • US20140067832A1
    • 2014-03-06
    • US13630325
    • 2012-09-28
    • Digvijay Singh LambaXiaoyong Chai
    • Digvijay Singh LambaXiaoyong Chai
    • G06F17/30
    • G06F17/2785G06F17/277G06F17/2795G06F17/30654G06F17/3069G06F17/30734
    • Disclosed are methods for returning to a user an answer to the question “what is .” Concepts and classes to which the concepts belong are determined from a corpus, such as taxonomy. The concepts are mapped to categories according to the structure of the taxonomy. Homonyms for words are collected and scored according to likeliness of use. Concept vectors are assembled for the identified concepts based on articles in the corpus and social media usage. Words are evaluated for generic-ness and a generic score is associated therewith. In responding to a query, the generic-ness of the terms of the query is evaluated and additional context solicited if the terms are generic. Candidate homonym concepts for a string in the query are selected according to context vectors for the homonym concepts. One or more homonym concepts are selected and the one or more categories corresponding to these concepts are returned.
    • 公开的是向用户返回“什么是”的答案的方法。 概念所属的概念和类从语料库确定,如分类法。 概念根据分类结构映射到类别。 词的同义词根据使用的可能性进行收集和评分。 基于语料库和社交媒体使用中的文章,针对识别的概念组合概念向量。 对于通用性进行评估,并且通用分数与之相关联。 在响应查询时,如果术语是通用的,则对查询的条款的通用性进行评估,并附加附加内容。 根据和声概念的上下文向量选择查询中的字符串的候选和声概念。 选择一个或多个同音符概念,并且返回与这些概念对应的一个或多个类别。
    • 15. 发明授权
    • Interest expansion using a taxonomy
    • 利用分类法扩大兴趣
    • US09020962B2
    • 2015-04-28
    • US13650077
    • 2012-10-11
    • Digvijay Singh LambaXiaoyong Chai
    • Digvijay Singh LambaXiaoyong Chai
    • G06F17/30
    • G06F17/30734G06F17/30702G06F17/30867
    • Disclosed are methods for inferring interests of a user based on declared interests of the user. Text for which a user has expressed interest, e.g. “liked” is evaluated to identify at least one principal concept. A principal article for the principal concept is located in a taxonomy and the link structure of the taxonomy analyzed to identify candidate articles related to the principal article. The candidate articles are scored according to a plurality of metrics and these scored are weighted and combined for a final score. Candidate articles are selected for the score and recommendations are generated and recommendations generated based on the concepts of the selected candidate articles.
    • 公开的是基于用户声明的兴趣来推断用户兴趣的方法。 用户表示兴趣的文字,例如 评估“喜欢”以确定至少一个主要概念。 主要概念的主要文章位于分类学中,并分析了分类学的链接结构,以确定与主要文章相关的候选文章。 候选文章根据多个度量进行评分,并且对这些评分进行加权并组合以获得最终得分。 选择候选文章以获得分数,并根据所选择的候选文章的概念生成建议和建议。
    • 16. 发明申请
    • IDENTIFYING PRODUCT REFERENCES IN USER-GENERATED CONTENT
    • 识别用户生成的内容中的产品参考
    • US20140149105A1
    • 2014-05-29
    • US13688060
    • 2012-11-28
    • Digvijay Singh LambaXiaoyong ChaiNicole Whisler
    • Digvijay Singh LambaXiaoyong ChaiNicole Whisler
    • G06F17/27
    • G06F17/2765G06F17/277
    • Systems and methods are disclosed herein for extracting products referenced in a document. A document is analyzed to identify a product type that is referenced in the document. Attributes are extracted from the document. A set of candidate products are identified corresponding to the extracted attributes. A score is calculated for the candidate products and the products are further selected or filtered based on the score, whitelist rules, and blacklist rules in order to identify one or more inferred products referenced by the document. The whitelist and blacklist rules may take as inputs a domain, a user identifier, and keywords included in the document. A set of sufficient attributes may be identified for each product type. Selection of a candidate product may be based at least in part on the document including all of the attributes in the set of sufficient attributes.
    • 本文公开了用于提取文献中引用的产物的系统和方法。 分析文档以识别文档中引用的产品类型。 属性从文档中提取。 根据提取的属性识别一组候选产品。 计算候选产品的分数,并根据分数,白名单规则和黑名单规则进一步选择或过滤产品,以便识别由文档引用的一个或多个推断产品。 白名单和黑名单规则可以将文档中包含的域,用户标识符和关键字作为输入。 可以为每种产品类型识别一组足够的属性。 候选产品的选择可以至少部分地基于包括所述一组充分属性中的所有属性的文档。
    • 17. 发明申请
    • TRANSFORMING A GRAPH TO A TREE IN ACCORDANCE WITH ANALYST GUIDANCE
    • 根据分析指南将图形转换为树
    • US20140082022A1
    • 2014-03-20
    • US13622975
    • 2012-09-19
    • Digvijay Singh LambaOmkar Deshpande
    • Digvijay Singh LambaOmkar Deshpande
    • G06F17/30
    • G06F17/30958G06F17/30961
    • Methods are disclosed for converting a directed graph to a taxonomy using guidelines from a user. An initial tree is output from a first pruning step in which subtree preferences (and other weights) are applied to preserve or remove paths from a node to one or more levels of descendent nodes. Subtree preferences (and infoboxes) may specify rules for automatically generating recommendations during application to nodes. In a second pruning step, the directed graph is again processed with additional weightings applied to edges in the graph in accordance with the recommendations. The recommendations may be human defined. Recommendations may specify a recommended ancestor for a particular node and may include a weighting to be applied to the recommendation itself, if there are multiple conflicting recommendations for the same node. Recommendations may also specify what standard weight to apply to the edge of the best parent.
    • 公开了使用来自用户的指南将有向图转换成分类法的方法。 从第一个修剪步骤输出初始树,其中应用子树首选项(和其他权重)以保留或删除从节点到一个或多个级别的后代节点的路径。 子树偏好(和信息框)可以指定在应用到节点期间自动生成建议的规则。 在第二个修剪步骤中,根据建议,再次对有向图进行处理,其中额外的加权应用于图中的边。 建议可能是人为的。 建议书可以为特定节点指定推荐的祖先,并且如果针对同一节点存在多个冲突建议,则可以包括要应用于推荐本身的加权。 建议书还可以规定适用于最佳父母边缘的标准体重。