Hiroshima University Syllabus

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Japanese
Academic Year 2024Year School/Graduate School Graduate School of Advanced Science and Engineering (Master's Course) Division of Advanced Science and Engineering Informatics and Data Science Program
Lecture Code WSN21001 Subject Classification Specialized Education
Subject Name 情報検索概論
Subject Name
(Katakana)
ジョウホウケンサクガイロン
Subject Name in
English
Information retrieval
Instructor KAMEI SAYAKA
Instructor
(Katakana)
カメイ サヤカ
Campus Higashi-Hiroshima Semester/Term 1st-Year,  First Semester,  2Term
Days, Periods, and Classrooms (2T) Mon5-8:ENG 115
Lesson Style Lecture Lesson Style
(More Details)
 
Presentation by students 
Credits 2.0 Class Hours/Week   Language of Instruction B : Japanese/English
Course Level 5 : Graduate Basic
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 02 : Information Science
Eligible Students
Keywords  
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students)
 
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students)
 
Class Objectives
/Class Outline
We are going to learn introduction to recommendation systems. 
Class Schedule lesson1 Guidance,
lesson2 An Introduction to Recommender Systems
lesson3 Neighborhood-Based Collaborative Filtering
lesson4 Model-Based Collaborative Filtering
lesson5 Model-Based Collaborative Filtering
lesson6 Content-Based Recommender Systems
lesson7 Knowledge-Based Recommender Systems
lesson8 Ensemble-Based and Hybrid Recommender Systems
lesson9 Evaluating Recommender Systems
lesson10 Context-Sensitive Recommender Systems
lesson11 Time- and Location-Sensitive Recommender Systems
lesson12 Structual Recommendations in Networks
lesson13 Social and Trust-Centric Recommender Systems
lesson14 Attack-Resistant Recommender Systems
lesson 15 Advanced Topics in Recommender Systems 
Text/Reference
Books,etc.
Charu C. Aggarwal, "Recommender Systems: The Textbook", Springer, 2016 
PC or AV used in
Class,etc.
 
(More Details) Textbook 
Learning techniques to be incorporated  
Suggestions on
Preparation and
Review
You have to give a presentation in the class. 
Requirements  
Grading Method Presentation, Resume, Questions and Answers. 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
Message  
Other   
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. 
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