Hiroshima University Syllabus

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Academic Year 2022Year School/Graduate School School of Informatics and Data Science
Lecture Code KA215001 Subject Classification Specialized Education
Subject Name データマイニング
Subject Name
Subject Name in
Data Mining
モリモト ヤスヒコ
Campus Higashi-Hiroshima Semester/Term 3rd-Year,  First Semester,  1Term
Days, Periods, and Classrooms (1T) Thur1-4:ENG 103
Lesson Style Lecture Lesson Style
(More Details)
Lecture and related exercises by using a computer
【Online/ondemand style class by using Bb9 and Teams】 
Credits 2.0 Class Hours/Week   Language of Instruction B : Japanese/English
Course Level 2 : Undergraduate Low-Intermediate
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 02 : Information Science
Eligible Students Senior Level
Keywords Knowledge Discovery, Information Retrieval, Discovery Science, Large-scale data processing, Big Data 
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Criterion referenced
Integrated Arts and Sciences
(Knowledge and Understanding)
・Knowledge and understanding of the importance and characteristics of each discipline and basic theoretical framework.
(Abilities and Skills)
・The ability and skills to collect and analyze necessary literature or data among various sources of information on individual academic disciplines.
・The ability and skills to specify necessary theories and methods for consideration of issues.

Informatics and Data Science Program
(Knowledge and Understanding)
・D1. Knowledge and skills required for understanding the theoretical system of statistics and data analysis, and for precisely and efficiently analyzing qualitative/quantitative information in big data.

(Abilities and Skills)
・A. Skills related to the development of an information infrastructure,information processing techniques, and technology for producing new added value through data analysis.
Class Objectives
/Class Outline
- To understand how to retrieve necessary information from stored databases efficiently and effectively
- To understand what is valuable information and how to extract valuable information
- To understand important issues for handling large-scale data 
Class Schedule 1-2: Guidance, Recent Data Innovation
3-4: Database Management
5-6: Association Rule
7-8: Numerical Association Rule
9-10: Prediction Model
11-12: Clustering
13-14: Big Data Platform
15: Data Mining Applications (CRM, Recommendation System, Search Engine, etc.) 
Reference Book:
Jiawei Han, Micheline Kamber共著「Data Mininig: Concepts and Technologies」(Morgan Kaufmann) 
PC or AV used in
(More Details) PowerPoint and Handout 
Learning techniques to be incorporated  
Suggestions on
Preparation and
Compute the results of sample databases by yourself and confirm the results and how they work. 
Grading Method Quiz and Exercise 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
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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