[New Electronic Resource] Airiti Library's New "Research Results Analysis Module" is Now Live!

Dear Faculty, Staff, and Students:

To enhance the academic research efficiency of our university's faculty and students, the library has introduced the upgraded "Research Results Analysis Module" for "Airiti Library" (formerly CEPS Chinese Electronic Periodical Services)!

Feeling overwhelmed by the vast sea of academic literature and not knowing where to start? The upgraded "Research Results Analysis Module" can perform rapid big data analysis and AI intelligent summarization on your search results after you retrieve academic literature. This module provides four key features to help you see both the forest and the trees when searching for data, significantly saving you time on literature organization:

🌟 Introduction to the Five Key Features:

  1. Highly Cited Literature (Accurately grasp core research): The system will filter and display the top 10 most cited important articles from your current search results. This data comes from the "ACI (Academic Citation Index) Database," which comprehensively collects citation literature from high-quality academic journals in Taiwan, Hong Kong, and Macau. With just one click, you can grasp the most influential landmark articles and authoritative authors.
    • ACI (Academic Citation Index) Database: Readers can not only understand bibliographies and browse references when searching for literature to grasp the contextual progression between articles, but also utilize the cross-linking relationships between citations to quickly find more related literature or identify high-impact, important publications.
  2. Keyword Analysis (Visualize research hotspots): The system will generate a "Word Cloud" for your search results, visually presenting the top 50 most frequent popular keywords. The larger, darker, and more centered the text is, the higher the frequency of the keyword. You can also directly click on the number link of a keyword to further filter for precise literature, easily grasping the latest research trends in the field.
  3. Apply for Batch Export (Meet large-scale bibliographic needs): If you need to export a large amount of bibliographic data during your research process, you can directly fill out the application information within the system and agree to the terms of data use. After a specialist confirms your needs, they will assist you in batch exporting the required bibliographic data.
  4. AI Assistant (AI literature review): Airiti Library has fully introduced generative AI technology! The "AI Assistant" will automatically fetch the top 10 most relevant articles from your search results, summarize the research topics, and write a literature review that echoes your search query theme. Making literature organization no longer time-consuming and laborious!
    • This is a point-based service. Each analysis deducts 1 point. The entire university shares 30 points per day, and the points are reset and updated daily.
  5. Japanese Journal Search: Partnering with Japan's J-STAGE and introducing real-time AI translation, allowing you to search for Japanese academic resources using Chinese directly within Airiti Library.

💡 How to use?

  1. Access Path: Go to and search for the database names "Airiti Library" and "ACI學術引用文獻資料庫".
  2. Please enter "Airiti Library" through the campus network or by logging into the off-campus connection. After performing an "Academic Literature" search, you will see an analysis block at the top of the search results page containing function tabs such as "Highly Cited Literature," "Keyword Analysis," "Apply for Batch Export," and "AI Assistant."

🎞️ Tutorial Videos

  1. Highly Cited Literature, Keyword Analysis, Apply for Batch Export: https://youtu.be/Zu_i0PwJv8Y?si=zb5BrewR9F_9I275
  2. Japanese Journal Search: https://youtu.be/q3EXib_OSt8?si=W5ij-lWTQ_pQkAAf
  3. AI Assistant: https://youtu.be/YdzcT5Gb51o?si=8JLHsfzDtpCxqd6o

📅 Access Period: October 16, 2026, to October 15, 2027

📢 Bonus Promotion: [Trial Electronic Resource] Airiti Library AI Module (Natural Language), URL: https://lib.mmu.edu.tw/p/406-1000-3332,r20.php?Lang=zh-tw