| Academic Year |
2026Year |
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 |
| Lesson Style |
Lecture |
Lesson Style (More Details) |
Face-to-face |
| Presentation by students |
| Credits |
2.0 |
Class Hours/Week |
4 |
Language of Instruction |
J
:
Japanese |
| Course Level |
5
:
Graduate Basic
|
| Course Area(Area) |
25
:
Science and Technology |
| Course Area(Discipline) |
02
:
Information Science |
| Eligible Students |
|
| Keywords |
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| 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. |
Microsoft Teams |
| (More Details) |
Textbook |
| Learning techniques to be incorporated |
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Suggestions on Preparation and Review |
You have to give a presentation in the class. |
| Requirements |
|
| Grading Method |
Presentation, Resume, Questions and Answers. |
| Practical Experience |
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| Summary of Practical Experience and Class Contents based on it |
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| Message |
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| 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. |