用定量转换增强 NLP:数字语言资源产业愿景

المعتز بالله السعيد
{"title":"用定量转换增强 NLP:数字语言资源产业愿景","authors":"المعتز بالله السعيد","doi":"10.21608/mjoms.2024.293375.1165","DOIUrl":null,"url":null,"abstract":": Natural Language Processing (NLP) has transformed human-machine communication in the digital age, enhancing productivity and unlocking a wealth of possibilities. The effectiveness of NLP hinges on the availability of robust digital resources, such as extensive lexical databases and real-world language corpora. These resources are crucial for various NLP applications, including machine translation, text mining, and speech recognition. NLP's advancements hold immense promise to bridge communication gaps across cultures, provide deeper linguistic insights, and boost productivity across sectors, impacting education, industry, and economic development. However, challenges such as ethical concerns, the necessity for high-quality data, and potential biases in digital language resources must be addressed. This paper presents a vision for the digital resource industry as the cornerstone of NLP, focusing on quantitative transformations that tackle NLP challenges and facilitate big data management. Embracing these transformations, along with a robust digital resource industry, can significantly enhance human-machine interactions and drive future innovations.","PeriodicalId":254738,"journal":{"name":"مجلة جامعة مصر للدراسات الإنسانية","volume":"1 4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhancing NLP with Quantitative Transformations: A Vision for the Digital Language Resources Industry\",\"authors\":\"المعتز بالله السعيد\",\"doi\":\"10.21608/mjoms.2024.293375.1165\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": Natural Language Processing (NLP) has transformed human-machine communication in the digital age, enhancing productivity and unlocking a wealth of possibilities. The effectiveness of NLP hinges on the availability of robust digital resources, such as extensive lexical databases and real-world language corpora. These resources are crucial for various NLP applications, including machine translation, text mining, and speech recognition. NLP's advancements hold immense promise to bridge communication gaps across cultures, provide deeper linguistic insights, and boost productivity across sectors, impacting education, industry, and economic development. However, challenges such as ethical concerns, the necessity for high-quality data, and potential biases in digital language resources must be addressed. This paper presents a vision for the digital resource industry as the cornerstone of NLP, focusing on quantitative transformations that tackle NLP challenges and facilitate big data management. Embracing these transformations, along with a robust digital resource industry, can significantly enhance human-machine interactions and drive future innovations.\",\"PeriodicalId\":254738,\"journal\":{\"name\":\"مجلة جامعة مصر للدراسات الإنسانية\",\"volume\":\"1 4\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"مجلة جامعة مصر للدراسات الإنسانية\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21608/mjoms.2024.293375.1165\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"مجلة جامعة مصر للدراسات الإنسانية","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21608/mjoms.2024.293375.1165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

:自然语言处理(NLP)改变了数字时代的人机交流,提高了工作效率,开启了无限可能。NLP 的有效性取决于是否有强大的数字资源,如广泛的词库和真实世界的语言库。这些资源对于机器翻译、文本挖掘和语音识别等各种 NLP 应用至关重要。NLP 的进步为弥合不同文化间的交流鸿沟、提供更深入的语言洞察力、提高各行各业的生产力、影响教育、工业和经济发展带来了巨大希望。然而,诸如伦理问题、高质量数据的必要性以及数字语言资源中的潜在偏见等挑战必须得到解决。本文提出了数字资源产业作为 NLP 基石的愿景,重点关注解决 NLP 挑战和促进大数据管理的定量转型。拥抱这些变革,再加上一个强大的数字资源产业,可以极大地增强人机互动,推动未来的创新。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing NLP with Quantitative Transformations: A Vision for the Digital Language Resources Industry
: Natural Language Processing (NLP) has transformed human-machine communication in the digital age, enhancing productivity and unlocking a wealth of possibilities. The effectiveness of NLP hinges on the availability of robust digital resources, such as extensive lexical databases and real-world language corpora. These resources are crucial for various NLP applications, including machine translation, text mining, and speech recognition. NLP's advancements hold immense promise to bridge communication gaps across cultures, provide deeper linguistic insights, and boost productivity across sectors, impacting education, industry, and economic development. However, challenges such as ethical concerns, the necessity for high-quality data, and potential biases in digital language resources must be addressed. This paper presents a vision for the digital resource industry as the cornerstone of NLP, focusing on quantitative transformations that tackle NLP challenges and facilitate big data management. Embracing these transformations, along with a robust digital resource industry, can significantly enhance human-machine interactions and drive future innovations.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信