CSCI 7000-002 |
Fall 2010 |
| |
Systems and Algorithms for
Massive Data Applications |
Announcements
Administrative Information
Meeting time |
Tu Th 09:30am -- 10:45am |
Location |
ECCS 1B12 map |
Instructor |
Qin (Christine) Lv |
Phone |
(303) 492 - 8821 |
Fax |
(303) 492 - 2844 |
Email |
|
Office |
ECCR 1B05C |
Office hours |
Tu 11:00am - 12:00pm or by appointment. |
Course Description
This course presents a survey of recent research on
efficient system and algorithm design for managing and exploring
massive amounts of digital data. This course covers systems issues
such as search systems, storage systems, peer-to-peer systems,
mobile and sensor networks, as well as practical use of sketching,
indexing, and data mining techniques. Domain-specific data management
and analysis, such as those in finance, health, multimedia dan,
online social networks, bioinformatics, and scientific computing,
are also covered.
This course is open to both PhD students and MS/ME students.
Students are expected to read research papers, write paper reviews,
participate in discussions, present papers,
and finish a course project.
Course Schedule
Please see the
internal course website for the most up-to-date schedule.
Grading
Your performance will be measured in the following four ways:
- Paper review (30%)
- There are 2-3 papers in the readling list for each class.
You need to pick at least 15 papers from the lists and write a
review for each of them.
Your review may contain the following:
what is this paper about? what are its strengths and
weaknesses? is the description of the main technique
clear to you? are the evaluations (if any) reasonable
and convincing? can you improve their technique or apply
it to a different domain? ....
- Class participation (20%)
- Besides the paper you reviewed, you should also read
other papers in the reading list and be prepared to participate
in discussions at class.
- Paper presentation (10%)
- During the semester, you will be asked to give
two presentations. Each presentation is about 45 minutes
long. Check out the current
course schedule and pick a topic that you would like
to present. You may also suggest new topics/readings.
Each presentation also counts as a paper review, i.e.,
you do not need to submit a paper review for the topic
you are presenting.
- Course project (40%)
- Each student needs to finish a course project that is
related to the topics coverd in the course. Students can
pick their own projects. Project proposals are due in
Week 7. Project checkpoints are in Week 11. Final
project presentations and reports are due in Week 16.
Prerequisites
Graduate standing.
Textbook
No textbook is required. A list of research papers and other
reading materials will be provided.
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