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A Novel Framework For Future Natural Language Processing From A Database Perspective by Limin Zhang
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1A Novel Framework For Future Natural Language Processing From A Database Perspective
By Limin Zhang
A Novel Framework for Future Natural Language Processing From a Database Perspective 作者: Limin Zhang 1 作者单位: 1. Renmin University of China 提交时间: 2023-11-01 摘要: Most research and applications on natural language still concentrate on its superficial features and structures. However, natural language is essentially a way of encoding information and knowledge. Thus, the focus should be on what is encoded and how it is encoded. In line with this, we suggest a database-based approach for natural language processing that emulates the encoding of information and knowledge to build models. Based on these models, 1) generating sentences becomes akin to reading data from the models (or databases) and encoding it following some rules; 2) understanding sentences involves decoding rules and a series of boolean operations on the databases; 3) learning can be accomplished by writing on the databases. Our method closely mirrors how the human brain processes information, offering excellent interpretability and expandability. NLP NLU NLG Machine Learning 来自: Limin Zhang 分类: 计算机科学 >> 自然语言理解与机器翻译 投稿状态: 未投稿 引用: ChinaXiv:202311.00040 (或此版本 ChinaXiv:202311.00040V1 ) DOI:10.12074/202311.00040V1 CSTR:32003.36.ChinaXiv.202311.00040.V1 推荐引用方式: Limin Zhang.(2023).A Novel Framework for Future Natural Language Processing From a Database Perspective.中国科学院科技论文预发布平台.doi:10.12074/202311.00040V1 版本历史 [V1] 2023-11-01 10:33:54 ChinaXiv:202311.00040V1 下载全文
“A Novel Framework For Future Natural Language Processing From A Database Perspective” Metadata:
- Title: ➤ A Novel Framework For Future Natural Language Processing From A Database Perspective
- Author: Limin Zhang
“A Novel Framework For Future Natural Language Processing From A Database Perspective” Subjects and Themes:
- Subjects: ➤ ChinaXiv - 中国科学院科技论文预发布平台 - 计算机科学 - 自然语言理解与机器翻译 - NLP - NLU - NLG - Machine Learning
Edition Identifiers:
- Internet Archive ID: ChinaXiv-202311.00040V1
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