CS 784: Advanced Topics in Database Management Systems

Spring 2009, Wed/Fri 11:00-12:15pm, room 1257 COMP S&ST

Announcements

Midterm #1, Midterm #2, and Final of CS 784, Spring 2008. (The Spring 2008 offering had two midterms.) For our upcoming midterm, you should check out Midterm #1 above, and look at the first few IR-related questions in the Final.
We will have a midterm on Friday March 13, in class, at the usual time.
Welcome. Make sure you are on the class mailing list.

Instructor
AnHai Doan, contact information available from my homepage. Office hours: Wed 1:15-2pm and Fri 1:15-2pm, and by appointment (pls send email, thanks).

Course Description
The official name of this course is "Data models and Languages", a legacy name left over from the past. For this semester, what I intend to cover is interesting material that is not covered in 564 or 764, and that is relevant to research and industrial development going on today in the broad context of data management.

Basically,

CS 564 is "everything you should know so that you can get an industrial job working with relational databases",
CS 764 is "all the gory details you may (or may not) want to know about relational data management systems", and
CS 784 is "all the stuff beyond relational data (e.g., Web, text, data mining, data integration, data extraction) that you should know to broaden your data management knowledge or to work in the field as an advanced developer/researcher".

Prerequisites: Undergraduate knowledge of relational databases is highly recommended. If not, you should be willing to do a "crash course" on the topic in the first few weeks. The recommended books for the crash course are: The Cow Book, or The Complete Book.

Course Format
The course meets twice a week to discuss research papers. You are required to read the specified paper before each lecture and attend the lectures. There will be a midterm, a final, and a project.

Midterm: March 13, in class at usual time/room,
Final: date to be decided, in class at usual time/room,
Other important dates: Feb 4: no class; March 18, 20: no class, spring break; last class is May 8.

Grade: midterm: 30%, final: 30%, project: 35%, participation in the class: 5%.

Course Schedule
The paper list is below (may be revised slightly as the course progresses). Each paper will be covered in 1-2 lectures.

Intro to the class (read Sections 1-2 of the Cimple paper); also read this paper and this paper

IR / Web Search
IR overview
Web search, Pagerank
Web search, Google
Web search and RDBMS

Data Languages
Note: this part will form the foundation for you to study information extraction and integration.
On the universality of data retrieval languages
Deductive databases (Datalog), Ullman notes
Evaluation of recursive programs

Information Extraction
Managing information extraction
You can find the SIGMOD tutorial, from which I created the above lecture here.
Datalog applied to information extraction
Wrapper induction for information extraction

In case you want to read more:

Information Extraction: Distilling Structured Data from Unstructured Text, by Andrew McCallum.
Information Extraction, by Sunita Sarawagi.

Data Integration
Several chapters from a textbook-in-progress on data integration (I will send out the book draft shortly):

Overview, virtual integration (Chapters 1-2)
Query unfolding, query containment, and answering queries using views (Chapter 3. Read only 3.1, 3.2.1, 3.2.2 (skim 3.2.2 only), 3.3.1, 3.3.2, 3.3.3, 3.3.4 (read only the bucket algorithm in 3.3.4))
Describing data sources (Chapter 4. Read only 4.1, 4.2)
Creating semantic mappings (Chapter 5. Read only 5.1, 5.2, 5.3, 5.4, and the preamble of 5.5. Then read 5.6, and the first part of 5.9 (up to right before the headline "Searching a set of possible schema mapping"))
Data mapping (no reading, materials covered in the class)
Other integration approaches (Read this two-page statement).

In case you want to read more:

Data Integration: The Teenage Years, by Alon Halevy.
Why Your Data Won't Mix: Semantic Heterogeneity, by Alon Halevy.

Others
wiki/Web 2.0/mass collaboration and also the CACM survey paper (will be emailed to the class on Sunday or early Monday)
Keyword search over multiple RDBMSs
Data mining: association rules not covered, no need to read
Data mining: clustering not covered, no need to read
Column store vs. row store and hardware trends, DeWitt's note not covered, no need to read
Scalable Semantic Web data management using vertical partitioning

Project
By Fri Feb 27: each team pls send me an email listing the names and email addresses of team members. Each team is 1-2 persons.

By Wed Mar 4: each team pls send me an email briefly describing the project topic.