學年學期 Academic Year / Semester 105學年度第2學期 Spring Semester, 2017
科目代號 Course Code 753863001
開課單位 Course Department 資科三、資科四、資科碩一、資科碩二 MA Program of Computer Science, Second Year
課程名稱 Course Name (中 Ch.)網路搜索與探勘 (英 Eng.)Web Search and Mining
授課教師 Instructor 蔡銘峰 TSAI MING-FENG
職稱 Title 專任助理教授 Assistant Professor
選課人數 Number Registered 0人
學分數 No. of Credits 3.0
修別 Type of Credit 選修 Elective
先修科目 Prerequisite(s)
上課時間 Session 二EFG tue18-21
教室 Location 研究250204 250204 Research Building(250204)
點閱核心能力分析圖與授課方式比例圖
課程簡介 Course Description

This course includes the following two parts:

Part I: Web Search
• Evaluation
• Retrieval Model
• Language Model
• Link Analysis
• Web Crawling

Part II: Web Mining
• Classification
• Clustering
• Learning to Rank
• Recommendation

課程目標與學習成效 Course Objectives & Learning Outcomes

The purposes of this course includes the following points:

1) to provide an overview of Web Search and Mining related research;

2) to systematically review the core research topics in the field;

3) to show case the most recent research progress;

4) to give students enough training for doing research in the field and an opportunity to work on a research project.

每週課程進度與作業要求 Course Schedule & Requirements【請詳述:課程內容與指定閱讀/教學活動與課前、課後作業/學生學習投入時間(含課堂教學時數)】

1. (1 week) Introduction: Goals and history of Web Search and Mining; IR vs. Web Search; DM vs. Web Mining.
2. (2 weeks) Web Search 1 - Ranking Evaluation; Probabilistic Information Retrieval
3. (2 weeks) Web Search 2 - Language Model for Information Retrieval
4. (2 weeks) Web Search 3 - Processing Text: Text statistics; Link Analysis
5. (1 week) Web Search 4 - Web Crawling
6. (2 week) Web Mining 1 - Classification and Naive Bayes
7. (2 weeks) Web Mining 2 - Supported Vector Machines; K Nearest Neighbor
8. (2 weeks) Web Mining 3 - Clustering: Flat clustering and Hierarchical clustering
9. (2 weeks) Web Mining 4 - Clustering: K-Means Clustering; Clustering and Search
10. (2 weeks) Web Mining 5 - Recommendation: Content-based approaches; Collaborative Filtering

每週課堂教學時數: 3 小時
每週預習/複習時數: 3 小時

評分標準 /成績相關規定 Course requirements/Grading standards

Grading will be based on the following weighting scheme:
• Assignments: 25%
• Midterm Exam: 30%
• Projects: 45%
• Bonus (participation): <= 5%

授課教師Office Hours、地點Office Location

Office Hours: Tue. 1-2pm or by email arrangement
Office Location: 大仁樓 413 研究室

教學助理基本資料 Teaching Assistant Information

陳志明-政大、中研院 TIGP 國際學程博士班二年級

He will help grade assignments, prepare assignments, and answer students' questions.

指定/參考書目 Textbook & references (為維護智慧財產權,請務必使用正版書籍)

• Introduction to Information Retrieval, by C. Manning, P. Raghavan, and H. Schütze.
• Search Engines: Information Retrieval in Practice, by Bruce Croft, Donald Metzler, Trevor Strohman.
• Data-Intensive Text Processing with MapReduce, by Jimmy Lin and Chris Dyer.
• Hadoop: The Definitive Guide, by Tom White.

課程相關連結 Course related links

課程附件 Course attachments
課程進行中,是否禁止使用智慧型手機、平板等隨身設備。

需經教師同意始得使用


指定參考書目清單     圖書館指參系統      指定參考書說明      指定參考書相關處理要點