Instructor: Prof. Jung-Hsien Chiang (蔣榮先)
Course: Fri 2-4; Office Hour: Tue 2-4
Course Goals
To understand and be able to apply information retrieval technology in automated biomedical literature search. Students will participate in intensive computer programming projects and will enhance their skills via research to various search technologies. This course also includes paper presentation and final project as well. Students will be expected to complete all course requirements upon their participation.
Course Outline
- Introduction
- IR and Statistical Methods
- Knowledge Inference
- Heuristics Methods
- Knowledge Maps
- Time-series Prediction
- Rule Discovery
- Advanced Text Mining Models
- Visual Knowledge Maps
- Final Presentation
Textbook
Michael J. Kearns and Umesh V. Varizani, An Introduction to Computational Learning Theory, MIT Press., Cambridge, MA, 1994.
References
Grading Policy
Computer Assignment* 30%
Presentation** 20%
Final Course Project 50%
Note :
* 每位修課同學隔週須獨力完成一個程式專案，並上台展示(Each student was asked to do 5 software tool-based projects for different subjects bi-weekly.)
Followings are possible subjects for projects:
- Keyword-based full text matching
- Query expansion models
- Indexing models
- Image Retrieval
- Searching the PubMed Documents
** Each student requires to present 2 relevant papers by assignment.
Related Material
Syllabus
Lecture Note
Homework