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Project Examination This is the schedule
for the project examination. The deadline for submitting your project report
is Tuesday 11/2 12:00 noon. Project Proposal Guidelines You can find some guidelines for the project report here. Make sure that you start
the report early! Assignment 3 – Part 2 You can now download the second
part of Assignment 3. It is due on Wednesday 22/01 in class. Paper Presentation Guidelines The presentations will be evaluated based on the quality
of the presentation, and the comprehension of the material. The following are
some guideline, tips and advice for preparing your presentation. ·
You
have 20 minutes for the presentation. We will enforce the time limit and cut
you off if you have not completed on time. Ten more minutes will be allocated
for questions. We may randomly pick someone from the audience to ask a
question, so everyone should pay attention. ·
You
should prepare around 20 slides, given that a slide takes around a minute to
talk about on average. Break you presentation into thematic units. The
following flow is very common: 1. Motivate why the problem is important and
give a high level idea; 2. Define clearly the problem; 3. Present the main
idea and the fundamental algorithms; 4. Present the results (experimental or
theoretical or both); 5. Conclusion. ·
The
talk should be selfcontained. Do not assume that the audience has read the
paper, or some previous work that you consider known. Define all the concepts
you need and all the notation that you use. Refer only to related work that
you know. ·
Since
the time for the talk is short, you will need to focus on the important parts
of the paper and avoid going through all the details. The goal is to give a
summary of the paper and have a clear message. Just because you read all the
paper it does not mean that you should present everything. At the same time,
you should not skip important information. Focusing on the right part to
present is important since it shows that you understood the paper well. ·
Prepare
the slides carefully. Do not add too much text, and only the math symbols
necessary. Do not use full sentences, but rather keywords and short phrases.
Make sure the slides are readable and not too loaded. Never ever project
parts of the paper pdf. ·
Practice!
Good talks are the result of a lot of practice even if they seem spontaneous
and fun to the audience. Practice the talk several times, and time yourself
to make sure you are within the time bounds. Some fun advice on how to give a bad talk (and more) here. Project Proposal Guidelines The suggested length for the project proposal is 12
pages. In the header you should have the title of the project, the members of
the project and the URL of the web page of the project. The text body of the project should have three main
parts: 1.
Problem definition: Describe the goal of your project
and the question that you want to answer. Write a few words to motivate why it
is important. 2.
Methodology: Describe how you will address the
problem you defined. What are the steps you will take? Try to be as specific
as possible. 3.
Evaluation: Explain how you will evaluate your
work. Describe the experiments you plan to do and the dataset that will be
used. At the end of the proposal write down the paper that
you will present (full citation). Although it is not mandatory, we suggest that you write
the project proposal and the project report in English, so that it is
accessible to anyone to read. Project Topics You can now download the list of
project topics. Let us know of the topic you pick, and email or set up a
meeting to discuss the details. If you have your own project proposal please
contact us with your suggestion. The timeline for the projects is as follows:
Project Assignments: · Topic 1: Ερμιόνη
Μάστορα,
Δημήτρης
Ζαβαντής · Topic
2: Κωνσταντίνος
Νούλης,
Απόστολος
Κούτρας · Topic
3: Θωμαή Κόρκου,
Παπαδημητρίου
Κατερίνα · Topic
4: Λάμπρος
Βατσιλίδης · Topic
5: Ελευθερία
Λιούκα,
Θανάσης
Κουφούλης · Topic
6: Μαρία Σπάη,
Φάνης Γιάχος · Topic
7: Μικέλα
Κακαράντζα · Topic
10:
ΔανιήλΔημήτριος
Πρόσκος · Topic
11: Νικόλαος
Παροτσίδης ·
Topic 13: (Distributed Community Detection
at Different Time Scales) Δημήτριος Γεώργιος Ακεστορίδης ·
Topic 13: (TimeAware Link Prediction) Νικόλαος Χαλιάσος Assignment 3 – Part 1 You can now download the first
part of Assignment 3. The first part of Assignment 3 is due on Wednesday
08/01 in class. Instructions for Presentation The presentations will take place at the end of the
lecture on 27/11 in class. We will start at 4:00pm exactly. Each presentation
should not take more than 10 minutes + 5 minutes for questions. This will be
strictly enforced. The general structure for the presentation should be as
follows: ·
12
slides for describing the model (this is known so you should just sketch it) ·
12
slides per measurement that you did with your comments/findings ·
1
slide for conclusion. Assignment 2 The
assignment is due on Wednesday 27/11 in class. The goal of this assignment is
for you to familiarize yourself with network generation models. There will
be 4 groups of 4 people working on one of the following models: 1.
Configuration
model (i.e., graphs following a given degree sequences) Generate
power law degree sequences, for different exponents α, where 2 £ α £ 3 2.
Preferential
attachment and copying model 3.
Small
world (using the caveman and WattsStrogatz model) 4.
Forest
Fire Model You should
implement the model(s) and compute the following measures: (a) the
degree distribution (b) the
clustering coefficient (c) the
effective diameter You should prepare
the following: 1.
A
short writeup to be handed in at the beginning of the class. The writeup
should include: (a) A short report on your
implementation of the model reporting any assumptions that you have made (b)
Plots of (i) the degree distribution with the
number N of nodes, for N = 1,000 to 10,000 (ii) the clustering coefficient with
the number N of nodes for N = 100 to 1,000 (iii) the effective diameter with
the number N of nodes for N = 100 to 1,000 For
each of the above measures, draw at least three different plots for different
values of the input parameters of the corresponding model (for example of
parameters a and d for the copying model, or the exponent α of the powerlaw). You should choose
carefully the values of these parameters, so that the plots show how each of
them affects the corresponding measure. Provide a short
explanation/justification of the plots. 2.
A
short presentation (510min) to be presented in class. Form
groups, and send us an email with the members of the group and a ranking of
the models according to the group preference. Models will be handed out on
FirstComeFirstServe basis. Project Assignments: 1.
Configuration
Model: Μικέλα
Κακαράντζα,
Ερμιόνη
Μάστορα,
Δημήτρης
Ζαβαντής,
Λάμπρος
Βατσιλίδης 2.
Preferential
Attachment and Copying Model: Θωμαή
Κόρκου, Θανάση
Κουφούλη,
Ελευθερία Λιούκα,
Κατερίνα
Παπαδημητρίου 3.
Small World Models: Γιάχος
Θεοφάνης, Σπαή
Μαρία, Κούτρας
Απόστολος, Νούλης
Κων/νος 4.
Forrest Fire Model:
ΔημήτριοςΓεώργιος
Ακεστορίδης,
Νικόλαος
Παροτσίδης,
ΔανιήλΔημήτριος
Πρόσκος,
Νικόλαος
Χαλιάσος Assignment 1 The
assignment is due on Wednesday 6/11 in class. The goal of this assignment is
for you to apply the techniques we described in class for observing and
computing powerlaws. 1.
Choose
a graph dataset (you can find a list of such datasets at the Resources page).
The graph should have at least a few thousand nodes. 2.
Compute
the degree distribution and produce the following plots:
i.
The
degree distribution in linear (not loglog) scale
ii.
The
degree distribution in loglog scale
iii.
The
degree distribution in loglog scale using exponential binning
iv.
The
cumulative degree distribution in loglog scale.
v.
The Zipf plot (loglog scale) of the degree
distribution 3.
Compute
the exponent of the powerlaw distribution You can
read more about the different methods of plotting the distribution and
estimating the powerlaw exponent at: · M.
E. J. Newman, Power
laws, Pareto distributions and Zipf's law, Contemporary Physics Prepare a
short writeup to be handed in at the beginning of the class. The writeup
should include: 1.
A
short (12 sentences) description of the dataset 2.
The
plots (i) – (v) described above along with a few observations for each of
them. 3.
The
value of the exponent and how you derive it (briefly) 4.
Whether
the distribution follows the power law and why. 