챗GPT 관련 요약문에서 기술 신조어 추출과 단어 임베딩
ChatGPT-related Technology Neologism Extraction and Word Embedding in Paper Abstracts
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This study aims to analyze the recent innovative changes in LLMs related to ChatGPT through neologism extraction and word embedding analysis. To this end, this paper collects 26,010 abstracts of international academic papers related to ChatGPT from November 2022 to April 2024. It extracts and analyzes the neologisms appearing in these abstracts by focusing on acronyms. Acronyms are frequently used in scientific texts such as AI or ChatGPT. The paper also analyzes the characteristics of word embedding, which quantifies the semantic similarity of words in the abstracts and seeks to understand and utilize how new concepts and terms are introduced and spread in the field of natural language processing. This research is one proper methodology for knowledge discovery
Abstract
This study aims to analyze the recent innovative changes in LLMs related to ChatGPT through neologism extraction and word embedding analysis. To this end, this paper collects 26,010 abstracts of international academic papers related to ChatGPT from November 2022 to April 2024. It extracts and analyzes the neologisms appearing in these abstracts by focusing on acronyms. Acronyms are frequently used in scientific texts such as AI or ChatGPT. The paper also analyzes the characteristics of word embedding, which quantifies the semantic similarity of words in the abstracts and seeks to understand and utilize how new concepts and terms are introduced and spread in the field of natural language processing. This research is one proper methodology for knowledge discovery
참고문헌 (14)
- 전국민 AI 일상화 실행계획, "관계부처합동", 관계부처합동, ~ (2023)
- 나혜인, "국가R&D정보서비스 고도화를 위한 신문기사를 이용한 ChatGPT 도입 PEST 분석과 텍스트마이닝", 한국정보기술학회논문지, 21(10), pp.171~184 (2023)
- 나혜인, "Reddit 소셜미디어를 활용한 ChatGPT에 대한 사용자의 감정 및 요구 분석", 한국인터넷정보학회논문지, 25(2), pp.79~92 (2024)
- 홍영예, "영어학의 이해" (2003), 한국문화사
- Brandl, S., "Domain-Specific Word Embeddings with Structure Prediction", Transactions of the Association for Computational Linguistics, 11, pp.320~335 (2023)
- Caliskan, A., "Gender Bias in Word Embeddings: A Comprehensive Analysis of Frequency, Syntax, and Semantics", Proceedings of the 2022 AAAI, 2022, 156~170
- Iseni, A., "Most Common Neologisims which Emerged during and in the Wake of COVID-19", Anglisticum Journal of the Association-Institute for English Language and American Studies, 12(7), pp.32~39 (2023)
- Katamba, F, "English Words" (2005), Routledge
- Kwak, M., "Social Images Reflected through English and Korean Neologisms in the New Normal Era", The Journal of Studies in Language, 39(4), pp.431~445 (2024)
- Lejeune, G., "Character Based Pattern Mining for Neology Detection", Proceedings of the First Workshop on Subword and Character Level Models in NLP (2017), Copenhagen
- Plag, I, "Word-Formation in English" (2003), Cambridge University Press
- Shang, J., "Automated Phrase Mining from Massive Text Corpora", IEEE Transactions on Knowledge and Data Engineering, 30(10) (2018)
- Sullivan, C, "Clustering Words from Biased Contexts using Dimensionality Reduction", MA, pp.2020
- Veyseh, A. P. B., "Acronym Extraction and Acronym Disambiguation Shared Tasks at the Scientific Document Understanding Workshop", The second workshop on Scientific Document Understanding at AAAI, pp.1~6 (2022)