A State-of-the-Art of Semantic Change Computation
원문 초록
This paper reviews the state-of-the-art of semantic change computation, one emerging research field in computational linguistics, proposing a framework that summarizes the literature by identifying and expounding five essential components in the field: diachronic corpus, diachronic word sense characterization, change modelling, evaluation data and data visualization. Despite the potential of the field, the review shows that current studies are mainly focused on testifying hypotheses proposed in theoretical linguistics and that several core issues remain to be solved: the need for diachronic corpora of languages other than English, the need for comprehensive evaluation data for evaluation, the comparison and construction of approaches to diachronic word sense characterization and change modelling, and further exploration of data visualization techniques for hypothesis justification.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Capturing Visualization Design Rationale
VIS-Shepherd: Constructing Critic for LLM-based Data Visualization Generation
Mapping correlations and coherence: adjacency-based approach to data visualization and regularity discovery
OLAF: An Open Life Science Analysis Framework for Conversational Bioinformatics Powered by Large Language Models
Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language Models
nvAgent: Automated Data Visualization from Natural Language via Collaborative Agent Workflow
토론
이 논문과 연결된 포럼 글이 아직 없습니다.