The topic selection and analysis function of FanWenMeow utilizes data mining technology to track the research dynamics of the world's major academic databases in real time. The system analyzes the abstracts of 1,000,000+ papers in the past three years through NLP algorithms, establishes a popularity index evaluation model, and recommends the most valuable research directions for users. The specific workflow includes:
- Keyword heat analysis: calculating the annual growth rate of keywords in the field
- Cross-disciplinary identification: discovering emerging disciplinary convergences
- Gap field testing: locating segments that have not yet been fully researched
Test data show that the tutor adoption rate of the recommended topic selection by this function reaches 87%, which is significantly higher than the traditional manual search method. User feedback shows that the selected topics based on AI analysis have an increase of more than 20% in both defense pass rate and journal acceptance rate.
This answer comes from the articleFan Meow: an AI tool for quickly generating high-quality essays and academic documentsThe
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