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Producing datasets for representing terms and objects based on automated learning from text contents

机译:根据对文本内容的自动学习,生成用于表示术语和对象的数据集

摘要

A system and methods for creating data objects as symbolic or associative representations of terms or objects using machine-based methods are presented. A term can be a word or a phrase, which can also be the name of an object. For a given term, the methods analyze other terms associated with the term, and determine a set of terms or values to be attached to the term to form a dataset, either as a representation of the term, or as information about an object represented by the term, including various properties associated with the object. The methods include obtaining a group of text contents or non-natural language data contents, specifying a target term or symbol, and identifying contextual attributes of the target term or symbol. The contextual attributes include positional and distance attributes, as well as grammatical and semantic attributes.
机译:提出了一种使用基于机器的方法将数据对象创建为术语或对象的符号或关联表示的系统和方法。术语可以是单词或短语,也可以是对象的名称。对于给定的术语,这些方法分析与该术语相关的其他术语,并确定要附加到该术语以形成数据集的一组术语或值,以表示该术语或作为有关由表示的对象的信息该术语,包括与对象关联的各种属性。该方法包括获得一组文本内容或非自然语言数据内容,指定目标术语或符号,以及识别目标术语或符号的上下文属性。上下文属性包括位置和距离属性,以及语法和语义属性。

著录项

  • 公开/公告号US9880998B1

    专利类型

  • 公开/公告日2018-01-30

    原文格式PDF

  • 申请/专利权人 GUANGSHENG ZHANG;

    申请/专利号US201514948321

  • 发明设计人 GUANGSHENG ZHANG;

    申请日2015-11-22

  • 分类号G06F17/27;G06F17/30;

  • 国家 US

  • 入库时间 2022-08-21 12:55:05

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