University of Tsukuba | Grad. Scho. Syst. and Info. Eng. | Dept. Comp. Sci. | List of Courses
Hiroyuki Kitagawa, Toshiyuki Amagasa, Hiroaki Shiokawa
E-Mail H. Kitagawa: kitagawa (AT), T. Amagasa: amagasa (AT), H. Shiokawa: shiokawa (AT)
Office hours All: contact by email.
Cource# 01CH304
Area Software System
Basic/Advanced 専門科目
Course style Lecture (partially includes practice)
Term FallAB
Period Tuesday 3,4
Room# SB0110
Keywords Database, Data Mining, Advanced Data Management
Prerequisites Students are encouraged to have fundamental knowledge about databases and information retrieval.
relation degree program competence Knowledge Utilization Skills, Management Skills, Communication Skills, Research Skills, Expert Knowledge
Outline This lecture covers basic data engineering techniques and some advanced topics. First, we briefly review database technologies which are the basis of this lecture. Then we pick up major data mining techniques and advanced topics on graph data management. The lecture is given in English.
Course plan
Basic database technologies
We review basic database technologies including relational databases and object databases.
Data warehouse and OLAP
We talk about information integration, data warehouse, OLAP, and other releted concepts.
Basic concept of data mining
We explain background, purpose, and major techniques of data mining.
Association Rules
We explain association rules, apriori algorithm, and FP-Growth algorithm.
We learn the basic concept of clustering, followed by basic algorithms, such as K-Means, hierarchical clustering, density-based clustering. We also learn the basic approach for evaluating clustering results.
Graph Data Management
We learn advanced topics in graph data management.
Textbook Original texts will be distributed in the lecture.
References P. N. Tan, M. Steinbach, A. Karpatne and V. Kumar, Introduction to Data Mining, Pearson
Evaluation Evaluated based on final exam and quizzes.
TF / TA TF・TA: Hiroyoshi Ito
Misc. Lecture is given in English.