北海道大学 シラバス・成績入力システム／HOKKAIDO Univ. Entry System of Syllabi and Academic Records - シラバス印刷

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Hokkaido University Syllabus
Course Title
Knowledge Base
Subtitle

Instructor (Institution)
Masaharu YOSHIOKA ( Faculty of Information Science and Technology )Other Instructors (Institution)
Masaharu YOSHIOKA ( Faculty of Information Science and Technology )James Allan
Open To Other Faculties /Schools

Course TypeYear

2019

SemesterType of Class

LectureNumber ofCredits

1st Semester (SummerTerm)

Course Number

2151022Year of Eligible Students〜Eligible Department /Class
Numbering Code
Major Category Code
GIST_CSIT
Level Code6Middle Category CodeOther Information
GIST_CSIT 6110
Major Category Title
Graduate School of Information Science and Technology (Computer Science and Information Technology)
Level
Specialized Subjects (advanced) in graduate level (Master's Course and Professional Course)
Middle Category Title

1

Knowledge software science

Small Category CodeSmall Category Title

1

OK

Applied knowledge software science

Language TypeClasses are in Japanese.
Course list by the instructor with practical experiences

Key Words
Knowledge base, Database,Knowledge Discovery, Clustering,Semantic Web, Ontology,Information Retrieval,Information Extraction

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Course Objectives
Knowledge base is a system to store varieties of data and knowledge for utilizing them. Basic knowledge and techniques aboutknowledge base are lectured and methods for knowledge discovery and retrieval using web information are also presented.

Course Goals
Expected outcomes of the lecture is to understand. Utilization of database for storing knowledge. Knowledge discovery technique from large scale data. Information retrieval and extraction from Web texts.

Course Schedule
Semantic web and ontology: 4 lectures
Semantic web aims to utilizing web information by describing semantic information of the text that can be processed directly andindirectly by machines. Concept of semantic web and related techniques are lectured.
Information Retrieval: 5 lectures
Information retrieval is an important pre-process for knowledge utilization in texts. Information retrieval model, evaluation metrics, andquery operations are lectured.
Information extraction from Texts and its application: 4 lectures
Several techniques for extracting and utilizing information in the text are lectured. Especially, issues related to information extraction andsentiment analysis are presented.
Database for large scale data: 2 lectures
Introduction of NoSQL database and its application are lectured.

Homework
Basic knowledge of programming, and basics of database (relational database) are needed.

Grading System
Evaluation will be carried out by the using reports. There are two types of reports. One is for a short report for each class and the other isa final report for all of the classes.

Practical experience and utilization for classes

Condition of tasking the subject

Textbooks
講義資料を配布し、適宜参考書を示すが，教科書は用いない。 Original materials will be distributed, and references will be indicated inthe class.

Reading ListWebsites

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Website of Laboratory

Additional Information

Update
2019/01/31 11:57:54

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