[The method and application to construct experience recommendation platform of acupuncture ancient books based on...

Area of Science:

• Traditional Chinese Medicine
• Computational Linguistics
• Knowledge Engineering

Background:

• Ancient acupuncture texts contain valuable clinical knowledge.
• Manual data extraction from these texts is time-consuming and inefficient.
• A digital platform is needed to organize and analyze this information.

Purpose of the Study:

• To build a knowledge platform for acupuncture ancient books using data mining.
• To provide users with efficient retrieval services for acupuncture information.
• To enable intelligent analysis of diseases, meridians, acupoints, and treatment rules.

Main Methods:

• Utilized Oracle 10g database and JAVA for platform development.
• Applied data mining techniques: word segmentation, speech tagging, dependency analysis, rule extraction, similarity calculation, ambiguity analysis, and supervised classification.
• Implemented association mining and decision analysis for comprehensive data interpretation.

Main Results:

• The platform supports full-text retrieval, word frequency, and association analysis.
• Search results display frequencies of meridians, acupoints, and techniques.
• Quantified relationships between diseases, acupoints, and techniques using support degree and confidence coefficients.

Conclusions:

• The developed platform serves as a valuable reference for clinical acupuncture treatment.
• It aids in the selection of diseases, meridians, and acupoints.
• The platform enhances acupuncture and moxibustion education through accessible data analysis.