학술논문
Assessing the Ability of AI-Driven Natural Language Processing to Accurately Analyze Unstructured Text Data
Document Type
Conference
Author
Source
2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON) Smart Generation Computing, Communication and Networking (SMART GENCON), 2023 3rd International Conference on. :1-5 Dec, 2023
Subject
Language
Abstract
This technical abstract examines the ability of herbal language processing (NLP)-driven synthetic Intelligence (AI) to analyze unstructured textual content facts. Unstructured textual content records include information from assets with webpages, social media, emails, and consumer comments. They are widely used in sentiment evaluation, hazard detection, and entity extraction programs. NLP-pushed AI answers along with natural language knowledge (NLU), herbal language knowledge (NLG), and natural language understanding (NLP) are used to manner and examine unstructured textual content information. The analysis technique starts evolving with tokenizing the facts, breaking the textual content into smaller factors, including phrases and phrases. After tokenizing the statistics, the AI device discovers styles inside the records. Those styles can then discover the emotions and entities inside the data. NLU and NLG models are used to expand the facts' expertise by assigning sentiment and issue-level scores. The accuracy of NLP-driven AI is similarly progressed through more excellent complex fashions consisting of deep studying and reinforcement.