資訊工程研究所(Graduate Institute of Computer Science and Information Engineering)
課程名稱(英文)
Large-Scale Data Analysis and Search
課程代碼
4105516_01
授課教師：
邱志義
學分數
3
必/選修
選修
開課年級
碩博合開
先修科目或先備能力：
This is an introductory course, intended for senior undergraduate and graduate students. The prerequisites are courses on computer programming, algorithms, and linear algebra.
課程概述：
Teach students who want to learn the basic concepts and state-of-the-art of large-scale data analysis techniques and related applications in information retrieval and search, including clustering, quantization, hashing, representation, and indexing.
學習目標：
1. Learn how to formulate, experiment, and evaluate related methods when process.
2. Learn core concepts and theories of information retrieval and search.
3. Learn how to solve problems by machine learning and information retrieval alg
教科書：
課程大綱
分配時數
核心能力
備註
單元主題
內容綱要
講授
示範
隨堂作業
其他
Approximate nearest neighbor search
Basic concepts, indexing, reranking, and state-of-the-art methods
9
12345678
Product quantization
Basic concepts, optimized PQ, deep learning-based PQ
6
12345678
Clustering
K-means, EM algorithm, deep learning-based clustering
6
12345678
hashing
Random projection, supervised and unsupervised hashing
4.5
12345678
Dimensionality reduction
PCA, LDA, LLE, manifold learning, t-SNE
4.5
12345678
Applications
Cross-modal analysis and retrieval, Recommender systems
9
12345678
Project
Project introduction and result presentation
3
3
12345678
Paper presentation
Presenting selected top conference and journal papers
9
12345678
教育目標
1.具獨立從事學術研究或產品創新研發之人才
2.具團隊合作精神及科技整合能力，並在團隊中扮演領導、規劃、管理之角色
3.具自我挑戰與終身學習能力之人才
4.具有學術倫理、工程倫理、國際觀之人才
核心能力
1.具有資訊工程與科學領域之專業知識(Competence in computer science and computer engineering.)
2.具有創新思考、問題解決、獨立研究之能力(Be creative and be able to solve problems and to perform independent research.)
3.具有撰寫中英文專業論文及簡報之能力(Demonstrate good written, oral, and communication skills, in both Chinese and English.)
4.具策劃及執行專題研究之能力(Be able to plan and execute projects.)
5.具有溝通、協調、整合及進行跨領域團隊合作之能力(Have communication, coordination, integration skills and teamwork in multi-disciplinary settings.)
6.具有終身學習與因應資訊科技快速變遷之能力(Recognize the need for, and have the ability to engage in independent and life-long learning.)
7.認識並遵循學術與工程倫理(Understand and commit to academic and professional ethics.)
8.具國際觀及科技前瞻視野(Have international view and vision of future technology.)
具有資訊工程與科學領域之專業知識(Competence in computer science and computer engineering.)
為何有關：
Large-scale datasets are a trend in the digital age. How to efficiently process massive amounts of data has become an important area of expertise in modern information engineering and scientific fields.
達成指標：
Assessment Method:評量方法：
Midterm Exam期中考
Level 5: Score of 80 or above.
等級5：成績達到80分以上。
Level 4: Score of 70 or above.
等級4：成績達到70分以上。
Level 3: Score of 60 or above.
等級3：成績達到60分以上。
Level 2: Score of 50 or above.
等級2：成績達到50分以上。
Level 1: Score below 50.
等級1：成績未達50分。
評量工具(可複選)：
Assessment is based on examinations and reports.
2
具有創新思考、問題解決、獨立研究之能力(Be creative and be able to solve problems and to perform independent research.)
為何有關：
It allows students to apply what they have learned in class to solve problems.
達成指標：
Can the student complete the specific project/task?
評量工具(可複選)：
Project Creatio專題製作
Level 5: Score of 80 or above.
等級5：成績達到80分以上。
Level 4: Score of 70 or above.
等級4：成績達到70分以上。
Level 3: Score of 60 or above.
等級3：成績達到60分以上。
Level 2: Score of 50 or above.
等級2：成績達到50分以上。
Level 1: Score below 50.
等級1：成績未達50分。
6
具有終身學習與因應資訊科技快速變遷之能力(Recognize the need for, and have the ability to engage in independent and life-long learning.)
為何有關：
Large-scale datasets are a trend in the digital age. Students should develop self-learning abilities to enrich themselves as technology advances.
達成指標：
Can the student independently read papers and understand the latest technologies?
評量工具(可複選)：
Paper Report論文報告
Level 5: Score of 80 or above.
等級5：成績達到80分以上。
Level 4: Score of 70 or above.
等級4：成績達到70分以上。
Level 3: Score of 60 or above.
等級3：成績達到60分以上。
Level 2: Score of 50 or above.
等級2：成績達到50分以上。
Level 1: Score below 50.
等級1：成績未達50分。