Enhancing NLP with Quantitative Transformations: A Vision for the Digital Language Resources Industry | ||||
| مجلة جامعة مصر للدراسات الإنسانية | ||||
| Article 9, Volume 4, Issue 3, July 2024, Page 249-268 PDF (505.94 K) | ||||
| Document Type: المقالات العلمية. | ||||
| DOI: 10.21608/mjoms.2024.293375.1165 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Almoataz B. Al-Said  
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| جامعة القاهرة | ||||
| 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. | ||||
| Keywords | ||||
| Digital Language Resources (DLRs); Natural Language Processing (NLP); Text Mining; Deep Learning; Quantitative transformations | ||||
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