Year: 2024
Type: conference-paper
Abstract: Named Entity Recognition (NER, Named Entity Recognition) is a technique suitable for extracting specific information from unstructured data, which transforms the extracted annotated word sequences into a form more suitable for the downstream tasks of natural language processing, and is able to recognize entities with specific meanings in the text, including people's names, places' names, and company names. Meanwhile, NER technology can help market analysis, public opinion monitoring, and customer relationship management in economic data analysis. In this paper, we explore the NER entity recognition technique, which employs the bert-large-discriminator-finetuned-conll03-english model to recognize unstructured textual data as specific string entities and classify them into specific categories. Through experiments, we demonstrate that the technique helps companies to perform competitive analysis and optimize market research in real business scenarios.
Authors: Binxi Xu, Siyao Zheng
Institutions: The University of Sydney, Xiamen University
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4410250705