公开(公告)号：WO2017143096A1

公开(公告)日：2017-08-24

申请号：PCT/US2017/018220

申请日：2017-02-16

Applicant: LINKEDIN CORPORATION

Inventor： KENTHAPADI, Krishnaram ,  KAO, Kevin ,  LEE, Jeffrey Warren

IPC: G06F17/30

CPC classification number: G06F17/30675 ,  G06F17/30663 ,  G06F17/30684 ,  G06F17/30719 ,  G06F17/30958 ,  G06Q10/1053 ,  H04L67/306

Abstract: In an example embodiment, a method for selecting text snippets to display on a computer display is provided. A universal concept graph for phrases relevant to a search domain is created, the universal concept graph representing each phrase as a node and relationships between the phrases as edges between the nodes. A result in the search domain is represented as a subgraph of the universal concept graph by extracting a portion of the universal concept graph containing phrases contained in the result. Then, a score is produced for each node of the subgraph, the score based on a graph analysis algorithm applied to the subgraph. Then text snippets to display for the result are selected to be displayed based on the scores produced in the subgraph for phrases contained in the text snippets.

Abstract translation: 在示例实施例中，提供了一种用于选择文本片段以在计算机显示器上显示的方法。 创建与搜索域相关的短语的通用概念图，通用概念图将每个短语表示为节点，并且将短语之间的关系表示为节点之间的边缘。 通过提取包含在结果中的短语的通用概念图的一部分，将搜索域中的结果表示为通用概念图的子图。 然后，为子图的每个节点生成一个分数，该分数基于应用于子图的图分析算法。 然后根据文章片段中包含的短语在子图中生成的分数选择要显示结果的文本片段。

公开(公告)号：WO2017091340A1

公开(公告)日：2017-06-01

申请号：PCT/US2016/060488

申请日：2016-11-04

Applicant: LINKEDIN CORPORATION

Inventor： KENTHAPADI, Krishnaram ,  HOANG, Huan Van ,  ROTH, Zachary Mason

IPC: G06F7/00

CPC classification number: G06Q50/01 ,  G06F17/3053 ,  G06F17/30864 ,  G06F17/3087 ,  G06F17/30899

Abstract: A search engine optimization system is provided with an on-line social network system. The on-line social network system includes or is in communication with a search engine optimization (SEO) system that is configured to prioritize search terms (potential search terms) representing geographic locations, based on their respective predicted value to users. The value of a job-related search term is expressed as a priority score assigned to that search term. The SEO system generates priority scores for different search terms, using a probabilistic model that takes into account a value expressing how likely the search term is to be included in a search query, as well as other signals that are indicative of the relative importance of a location represented by the search term.

Abstract translation: 搜索引擎优化系统具有在线社交网络系统。 在线社交网络系统包括搜索引擎优化（SEO）系统或与之通信，搜索引擎优化（SEO）系统被配置为基于它们各自对用户的预测值来优先化表示地理位置的搜索项（潜在搜索项）。 作业相关搜索词的值表示为分配给该搜索词的优先级分数。 SEO系统使用概率模型为不同的搜索词生成优先分数，该概率模型考虑了表示搜索词包括在搜索查询中的可能性的值，以及表示相对重要性的其他信号 位置由搜索字词表示。

公开(公告)号：WO2017151899A1

公开(公告)日：2017-09-08

申请号：PCT/US2017/020420

申请日：2017-03-02

Applicant: LINKEDIN CORPORATION

Inventor： KENTHAPADI, Krishnaram ,  BORISYUK, Fedor Vladimirovich ,  JAIN, Parul

IPC: G06F17/30 ,  G06N5/02 ,  G06N5/00 ,  H04L12/58 ,  G06Q50/00

Abstract: A machine may be configured to determining key concepts in documents. For example, the machine accesses a universal concept graph that includes a first set of nodes that represent concept phrases derived from internal documents associated with a social networking service (SNS) and external documents that are external to the SNS, and a first set of edges that connect a plurality of nodes of the first set of nodes. The machine accesses a content object associated with the SNS. The machine generates an induced concept graph associated with the content object based on an analysis of the content object and the universal concept graph. The machine identifies one or more key concept phrases in the content object based on applying one or more key concept selection algorithms to the induced concept graph. The machine stores the one or more key concept phrases in a record of a database.

Abstract translation: 机器可以被配置为确定文档中的关键概念。 例如，机器访问通用概念图，该通用概念图包括表示从与社交网络服务（SNS）相关联的内部文档以及SNS外部的外部文档导出的概念短语的第一组节点，以及第一组边缘 连接第一组节点的多个节点。 机器访问与SNS相关联的内容对象。 机器基于内容对象和通用概念图的分析生成与内容对象相关联的诱导概念图。 机器基于将一个或多个关键概念选择算法应用于诱导概念图来识别内容对象中的一个或多个关键概念短语。 机器将一个或多个关键概念短语存储在数据库记录中。