Name : Weiyi Meng
Office : N 4, Engineering Building
Telephone : 777-4311
Fax : 777-4729
Email: meng@cs.binghamton.edu
Web: http://www.cs.binghamton.edu/~meng/meng.html

Advanced topics in web data management. New techniques for retrieving documents from search engines, including the use of links and user behavior knowledge. Metasearch engine techniques including resource discovery and result fusion. Database approaches for web data management. Semistructured data management, including data models, query languages and XML. Data integration techniques and advanced access methods for Web Databases. The topics may vary when offered in different years.

When and where

Time : 8:30am --- 9:55am, Tuesday and Thursday
Classroom : FA-346

• Prerequisite: CS432/CS532 (Database Systems) or equivalent
• Co-requisite: CS533 (Information Retrieval) or equivalent

2:00pm --- 3:00pm, Tuesday, Thursday or by appointment

Name: TBA
Office hours: TBA
Office: TBA
Email: TBA

There will be no required textbook for this course. The course material will be from published research papers, technical reports, and lecture/tutorial notes.

• Topic 1: Introduction to Text Retrieval
• Topic 2: Search Engine Technology
• Topic 3: Metasearch Engine Technology
• Topic 4: Web Database Integration
• Topic 5: Managing Semi-Structured Data (if time available)

• One-two weeks will be used to introduce course projects.
• Two-three weeks will be used for students to make presentations about their projects. The instructor will lead discussions after presentations and all students are expected to actively participate in the discussions.
• The rest of the time will be lectures given by the instructor.

Every student will do a course project. It is yet to be decided whether the project will be a group project or an individual project.

A number of suggested projects will be provided by the instructor and these projects will be briefly discussed in the class. Students are encouraged to propose course projects.

• Midterm Exam: 15%
• Final Exam: 15%
• Class Participation: 10%. Class participation includes attendance and participation of class discussions. Student attendance is required and will be checked regularly by the instructor. Class participation will be graded by how regularly a student attends the class and how actively a student participates in the discussions.
• Presentation: 10%. Each student is required to present his/her course project to the entire class near the end of the semester. Presentation will be graded by the quality of the content, the quality of the slides and the smoothness and clarity of the presentation.
• Course Project: 50%. Several progress reports will be required by specified dates before the final report is handed in. Every progress report as well as the final report will be separately graded based on its quality of content (originality, creativity and technical content) and the quality of writing (organization, logic, clarity and readability).

Academic honesty and integrity are expected of every student. Dishonesty and cheating in all academic work related to this course, when discovered, will be severely punished. Please read the Student Academic Honesty Code at http://watson.binghamton.edu/acadhonorcode.html.

Students must write their reports by themselves and using their own languages. All referenced works (including ideas, algorithms, programs, etc.) must be clearly cited within the main body of the report and their full citations must be listed at the end of the report. Students' own contributions (new ideas, algorithms, programs, etc.) must be clearly identified.

• Cell phone: Cell phones must be turned off or in vibrate alert mode.
• Computer: Laptop/notebook computers should not be used in general and definitely not for unrelated activities.

The following are some of the leading journals and conferences related to the subject of this course:

• IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE)
• ACM Transactions on Information Systems (ACM TOIS)
• Very Large Data Base Journal (VLDB Journal)
• World Wide Web Journal
• World Wide Web Conference
• International ACM SIGIR Conference on Research and Development of Information Retrieval (ACM SIGIR)
• International Conference on Very Large Data Bases (VLDB)
• International Conference on the Management of Data (ACM SIGMOD)
• IEEE International Conference on Data Engineering (ICDE)

• DBLP site
• Google Scholar site
• CiteSeer site
• ACM Digital Library site
• IEEE Digital Library site