A review on the novelty measurements of academic papers
–arXiv.org Artificial Intelligence
Novelty evaluation is vital for the promotion and management of innovation. With the advancement of information techniques and the open data movement, some progress has been made in novelty measurements. Tracking and reviewing novelty measures provides a data-driven way to assess contributions, progress, and emerging directions in the science field. As academic papers serve as the primary medium for the dissemination, validation, and discussion of scientific knowledge, this review aims to offer a systematic analysis of novelty measurements for scientific papers. We began by comparing the differences between scientific novelty and four similar concepts, including originality, scientific innovation, creativity, and scientific breakthrough. Next, we reviewed the types of scientific novelty. Then, we classified existing novelty measures according to data types and reviewed the measures for each type. Subsequently, we surveyed the approaches employed in validating novelty measures and examined the current tools and datasets associated with these measures. Finally, we proposed several open issues for future studies.
arXiv.org Artificial Intelligence
Jan-29-2025
- Country:
- Asia > China
- Jiangsu Province > Nanjing (0.04)
- Europe > United Kingdom
- England > Oxfordshire > Oxford (0.04)
- North America > United States
- Illinois > Cook County
- Chicago (0.04)
- Massachusetts > Middlesex County
- Cambridge (0.04)
- New York > New York County
- New York City (0.04)
- Illinois > Cook County
- Asia > China
- Genre:
- Overview (0.87)
- Questionnaire & Opinion Survey (0.87)
- Research Report > New Finding (1.00)
- Industry:
- Technology:
- Information Technology
- Artificial Intelligence
- Machine Learning > Neural Networks (0.93)
- Natural Language > Text Processing (0.67)
- Representation & Reasoning (1.00)
- Data Science (0.67)
- Information Management (0.93)
- Knowledge Management (0.93)
- Artificial Intelligence
- Information Technology