Location: WH 311 Time: ThTh 3:30 - 4:50pm
Instructor:
Dr. Chris Ding, 529 ERB, Phone: 817-272-7041.
Email: chqding@uta.edu
Office Hours:
TuTh 1:00 - 3:00 (and stop-by anytime).
TA :
Miao Zhang, 407 ERB.
Email: miao.zhang@mavs.uta.edu
Office Hours:
MW 2:00 - 4:00
Final Exam: Wed Dec 5
- Contents and Objectives:
-
The new and booming Internet Information Technology industry
includes Search Engine companies such as Google, Bing;
Social Networks companies such as Facebook;
emerging companies for Text analysis systems,
Recommendation Systems, Question & Answering systems,
and companies such as Amzon.com, Ebay , etc, with primarily online customers.
This course is to prepare students either
(1) to enter this new Internet IT industry;
or (2) to do research on key technologies in this new IT industry.
The main topics covered will be
Social Networks, Small world networks, and
basic random graph models and graph algorithms;
Web analytics, Power laws, main algorithms,
Search Engine related algorithm such as
ranking, data log mining, query suggestion,
ad placing, community finding;
Recommendation Systems and main algorithms such as content analysis and collaborative filtering; basic Question and Answering systems.
Completion of this course will enable students to build a solid foundation in this new Internet Technology area and ready to projects/research in this area.
Complex networks such as the Web, social networks, protein interaction
networks, become increasingly important. Much advances are made in the
last decade in research and applications. This course covers some major
progress in this rapidly involving field.
This course will have homeworks,
class projects and present them in class;
one exam.
- Prerequisites:
-
No prerequisites.
But knowledge of Computer Algorithms, Graphs,
Data Mining, Machine Learning, Pattern Recognition, and
Statistics will help digest the course materials.
Course Schedule and Outline
Homework
Course Projects
- Textbook & References:
-
1. Networks, Crowds and Markets, by D. Easley & J. Kleinberg, 2010.
(online)
2. Networks, by M. Newman, 2010.
3. Introduction to Information Retrieval, by C. Manning, P. Raghavan,
H. Schütze. 2009.
(online)
4. Web Data Mining, by B. Liu. 2nd edition. July 2010.
5. A Tutorial on Social Networks by H. Liu, 2009.
(online)
- Grades
-
-
Final Exam --- 40%
-
Two Class projects --- 40%
-
Homework --- 10%
-
Class participation --- 10%
Attendance
Attendance is not mandatory, but is HIGHLY encouraged.
Americans With Disabilities Act
The University of Texas at Arlington is on record as being committed to both the spirit and letter of federal equal opportunity legislation; reference Public Law 93112 -- The Rehabilitation Act of 1973 as amended. With the passage of new federal legislation entitled Americans With Disabilities Act - (ADA), pursuant to section 504 of The Rehabilitation Act, there is renewed focus on providing this population with the same opportunities enjoyed by all citizens.
As a faculty member, I am required by law to provide "reasonable accommodation" to students with disabilities, so as not to discriminate on the basis of that disability. Student responsibility primarily rests with informing faculty at the beginning of the semester and in providing authorized documentation through designated administrative channels.
Academic Dishonesty
It is the philosophy of The University of Texas at Arlington that academic dishonesty is a completely unacceptable mode of conduct and will not be tolerated in any form. All persons involved in academic dishonesty will be disciplined in accordance with University regulations and procedures. Discipline may include suspension or expulsion from the University.
"Scholastic dishonesty includes but is not limited to cheating, plagiarism, collusion, the submission for credit of any work or materials that are attributable in whole or in part to another person, taking an examination for another person, any act designed to give unfair advantage to a student or the attempt to commit such acts." (Regents’ Rules and Regulations, Part One, Chapter VI, Section 3, Subsection 3.2, Subdivision 3.22)
Student Support Services Available
The University of Texas at Arlington supports a variety of student success programs to help you connect with the University and achieve academic success. These programs include learning assistance, developmental education, advising and mentoring, admission and transition, and federally funded programs. Students requiring assistance academically, personally, or socially should contact the Office of Student Success Programs at 817-272-6107 for more information and appropriate referrals.
2001-08-20