CSCI 4152/6509 - Course Project
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The course project for graduate students (CSCI 6509) should follow the
basic structure of a typical research project, such as the research
work on a thesis, only on a smaller scale.
The undergraduate students (CSCI 4152) can choose as well to do a
research project, or they can do a more purely implementation-focused
You can form project teams of up to four students, or work
The final paper should be in the form of a technical report.
The presentations will be up to 8 minutes long, followed by 4 minutes
for questions. The graduate students (CSCI6509) will give individual
presentations, while undergraduate students (CSCI4152) can give
individual presentations or team presentations.
Regarding presentation dates, please take a look at the free time slots on
the course calendar and let me know by email your preference.
The presentations will be scheduled based on first-come-first-served
- P0 – project topic proposal, by email, due on Monday, Feb 2, 2015,
- P1 – a project statement, by email, due on Friday, Mar 2, 2015,
- P – oral presentation, book time slot early, submit slides
or slides overview (PDF or PPT) using SVN 24h ahead, and
- R – project report, submit using SVN, due on Monday, Apr 10, 2015.
Note about emails: All emails related to the course must have
the course number included in the subject,
such as CSCI4152, CSCI6509, or, the best option, CSCI4152/6509.
In more details, your subject lines for two required emails must be:
- CSCI4152/6509: Presentation time
- CSCI4152/6509: P0 submission
- CSCI4152/6509: P1 submission
- CSCI4152/6509: Presentation slides
- CSCI4152/6509: Project report
P0 – Project Topic Proposal
Worth: 1% of the final mark.
You will need to choose a topic for your project.
By the due date, you need to send to the instructor an email in plain
text with the following information:
the list of team members, and
one paragraph description of the topic.
Please do this as soon as you have chosen a topic. If two or more
students or groups have the same or
very similar topics, the one that sends P0 later may be required to change
the topic. If the topic is not sufficiently relevant to the course,
you may be asked to change it.
P1 – Project Statement
For CSCI6509: 5% of the final mark, and for CSCI4152: 3% of the
The project statement must be submitted using SVN. One member of the
group should submit it by creating subdirectory p1 in their SVN
directory and submitting the document in this directory. (If more
than one member of a group submit the document, it is not an error,
but only one document, randomly chosen, will be marked.)
The project statement should be in PDF format. If you want, you can
also submit additional documents (such as Word or LaTeX version, or a
plain text version).
The P1 document should be about 2 pages long.
It must include:
The statement should identify a feasible project.
P1 will be marked based on its completeness, clarity of presentation,
and research on and analysis of related work.
- Project title,
- Names of the member(s) of the group,
- Problem statement,
- List of possible approaches with citations to relevant work,
- Project plan for the rest of the term, and
- List of references.
P – Oral Presentation
Worth: 10% of the final mark, including class participation.
You are required to submit the slides of the presentation at least
24 hours before your presentation
using SVN in a subdirectory named "presentation".
The slides can be original slides, or an slides handout (e.g., 6 slides per page),
and they must be in a PowerPoint or PDF format. I will assume that you will use your
computer for presentation, but if you need a computer you can use the instructor's computer.
If you use the instructor's computer, you can only use PDF or
PowerPoint slides, without use of Internet or
running any other programs.
The presentations should last up to 8 minutes, with 4 additional
minutes reserved for questions and changing speakers, for the total of
There is a significant flexibility in choosing the topic of your presentation, but it
should be related to the project. It could be the work you have done up
to that time, or what you plan to do. It is a good idea to include
research or other related work that you did so far. You could also
present a related method from the textbook or another paper.
Evaluation scheme for presentations:
- content: how interesting and valuable is the presentation,
appropriateness of the topic, appropriateness for the audience and
the time allocated,
- presentation: clarity, eye contact with the audience; it should
be vivid, interesting; it is not a good idea to read from a paper, or from
the slides; avoid looking too much to the slides rather than to the
audience; do not just present to one person (e.g., instructor) -- talk to the whole audience,
organization and structure of the presentation should be well-planned;
time length should be appropriate,
- slides: organization of the presentation; slides content: appropriate
amount of text, use of figures,
- question answering: listening and answering the questions being asked,
appropriate answers, answering the actual question to the point,
but not going into a too lengthy additional discussion.
R – Project Report
Worth: grads 24% / ugrads 16% of the final mark.
The written project report is submitted in printed and electronic
form; i.e., in class and using SVN.
The reports are kept in archive with the instructor for several years.
A typical structure of a research project is:
This structure is just a guideline and parts may not be relevant to
your project. There are no fixed requirements about the length of the paper, since it
may depend on the type of the project and number of people in a group.
It is expected that a project report contains at least 8 pages, and it may be sufficient for an
A+ project if some implementational or experimental work has been done.
- Title, Author, Course name,
- Abstract – make sure it is an abstract of the whole paper and not
just a part of the introduction. The abstract should be brief,
definitely not longer than a half of a page.
- Introduction – introduce the problem; get a reader's attention;
explain motivation and significance of the problem,
define paper objectives. It is said
that the title, abstract, introduction, and the whole paper
should in a way express the same story in 10, 100, 1000, and
10,000 words, respectively. (Do not take these numbers literally!)
- Related Work – cover related work. Has this topic been
studied yet? Do not just give an annotated list of citations. Give a critical
analysis of the previous work.
- Problem Definition and Methodology – there is no good
research without a research problem. Define it precisely. Describe
your methodology, algorithms, system overview, or similar.
- Experiment Design – experiments are not mandatory, but some
form of evaluation of your approach should exist.
Evaluation, Discussion of evaluation results
Some Project Report Style Notes
The project report should be written in a good style from a technical
Computer Science perspective. This is a bit loose specification. A
couple of additional hints are provided below:
- use of a readable serif font in the main body of the text., font
- justified text in the main body (not ragged right, for example),
An example of how to choose a project topic and work on it
- Choose an NLP-related problem that is important and interesting
in your opinion. You should have some ideas about how it could
be solved, and about what interesting results you could obtain
by the end of term. The discussed problem should be
feasible in this sense, but it should not be trivial.
- The next step is to search through existing published work and
find out about existing solutions on the same problem, or to the
closest similar problem. You can start with the textbook.
- Design your method, implement it, and run experiments; possibly
try method variations.
- Analyze results. Revisit your methodology if needed.
- Finish the report. Keep writing during the term.
While the above guidelines describe a typical research project in NLP,
you can also consider some alternative forms:
Alternative Project Types
- theoretical project: You can focus on establishing a
formal framework and proving theoretical results, usually
regarding algorithm complexity of some solutions. Still, it may
be a good idea to have some experimental results even in this
type of project. This kind of project is still very research-oriented.
- implementation: You can put more emphasis on
the implementational part of the project. This usually means
developing a system prototype with multiple functionalities.
In this case, you can devote more space in your report to the
design, testing, and user documentation.
This kind of project could fit well undergraduate students, and they could
choose to implement some algorithm that is well-understood, and not necessarily
very relevant to the latest research.
- software evaluation: Choose one or more existing software
tools, download them, learn to use them, and use them to solve a
problem. Report on your evaluation of the tool, instructions
about its usage, advantages and limitations of the tool, and your
This kind of project is likely more appropriate for undergraduate students.
- survey: The survey format is a critical review of the current
research in a narrow sub-area of NLP. If you choose this option,
make sure that you do not cover a too wide, or already well-understood area,
with published surveys on the topic.
I would discourage you to go with this option, unless it is a
part of your wider research program. It is difficult to write a
good survey paper in a one-term time.
- NLP Research Links on the course web page
- http://acl.ldc.upenn.edu/ —
- Google scholar and other scientific Internet resources
Course Themes for This Term
These themes are chosen as themse for research and appliaction focus.
This means that some questions in assignments will be tageted towards
them, and if students do not feel strongly about any particular
topic for their project, they will be encouraged to work on these
problem areas. These themes are also related to to some current
research and industrial projects going on.
- Analysis of social media data, such as Twitter
- Author attribution and profiling
- Sentiment analysis
- Processing of email data
Topics of Some Previous Course Projects
The topics of some previous course projects are included in the
© 2002-2015 Vlado Keselj, last update: 22-Jan-2015