Collaborative Writing Tools for Predicting Verb Tense Using Syntax Parsing on Learning Networks

E. Mohammed, Z. A. Abutiheen, H. Hussein
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Abstract

Collaborative writing tools and Natural language processing are plays a vital role in learning networks. These tools are involved with the dealings among computer systems and human languages. It processes the data through syntax analysis, parsing and lexical analysis, and etc. Syntax analysis is used for syntactic parsing deals with the syntactic structure of a sentence. The collaborative writing tools and natural language processing applications are used for verb tense prediction and it it encodes the temporal order of activities in a sentence. Recognizing the syntactic structure is beneficial in identifying the means of a sentence. The model in this paper is introduced to predict verb tense based on lexical and syntactic features. This model works on English articles, every article will be split to sentences using the tokenization process. Every token in sentences will be analyzed and model will parse the sentences the use of tenses algorithms that represent grammar rules of the English language. This model is given precise accuracy when it is examined on articles/ stories.
在学习网络上使用句法分析预测动词时态的协作写作工具
协作写作工具和自然语言处理在学习网络中起着至关重要的作用。这些工具涉及计算机系统和人类语言之间的交易。它通过语法分析、解析和词法分析等方法对数据进行处理。语法分析是对句子的句法结构进行语法分析。使用协作写作工具和自然语言处理应用程序进行动词时态预测,并对句子中活动的时间顺序进行编码。认识句法结构有助于识别句子的意思。本文介绍了基于词汇和句法特征的动词时态预测模型。这个模型适用于英语文章,每篇文章将使用标记化过程拆分为句子。将分析句子中的每个标记,模型将使用表示英语语法规则的时态算法来解析句子。当对文章/故事进行检验时,该模型具有精确的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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