1. Indian Institute of Technology
Guwahati
A
nd
2 Edition
see inside
1
$ 3 2
dimension php security infinity pagerank chomp

2. Message from the
HoD
I am pleased to learn about the publica-
Rajen Kumar Sinha
tion of the second edition of Anantha the
magazine of MATRIX.
I am hopeful that the publication of this
edition will play an important role in the
dissemination of information on various
relevant academic activities within and
outside the department.
I invite the faculty, students and alumni to
send their views, opinions and write-ups
of academic nature for the purpose of
publication in the magazine. I hope their
contributions would be of great help to
the readers.
I congratulate the editorial team for their
great effort towards bringing out the
second edition, with the expectation that
this magazine will maintain a high stand-
ard of professionalism commensurate
with the academic goals of the depart-
ment.
1

3. 1
3
2 Pagerank Algorithm
Pagerank is an algorithm developed in the World Wide Web are taken as
by Sergey Brin and Larry Page (and nodes of a directed graph and each
hence the name pagerank) which is incoming hyperlink is taken as an
used to assign importance or rank to incoming edge. The number of
various pages on the World Wide incoming edges relate to the impor-
Web. This algorithm is one of the key tance of the page as perceived by
foundations of google search engine, other pages. If a page has been
but it is not the only one, it’s just one referred by many other pages
of the many indicators used by then that page is impor-
google to rank various pages and tant and must be
present them when searched for. The given a higher
algorithm in general may be priority.
applied to any set of Now let’s see
entities with cross how it works
references with an exam-
between ple. Suppose
the entities. for simplicity
It is a math- that there
ematical are only
algorithm 5 pages,
based on graph let them
theory. A higher be named A, B,
rank indicate more C, D and E. First of all
value is associated each of the pages is given
with that page and it an equal pagerank, 1/5 to each.
will be given priority Then for any page (let’s say A), the
(in terms ofposition in the pages which have a link to that par-
search results) to pages with rank ticular page (A in this case) are con-
lower to it. Pagerank works on the sidered (let them be C and D), and
assumption that a person surfing the the new pagerank of A is calculated
net clicks on the links randomly with- given by
out reading or thinking about what
the link has to offer and based on this PR(A) = PR(C) + PR(D)
it calculates the probability that such Here PR(i) refers to pagerank of page i.
a random surfer will land on a page. This is the most basic architecture.
The basic idea behind the whole Next taking into considerations some
algorithm is as follows. All the pages others factors, this basic form is
in the World Wide Web are taken as improved.
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4. Internship Experience
It was in March 2011 when I got the
An Experience that Remains
offer for the Amazon internship. With
thoughts juggling between the lures
and fantasies of a foreign internship
like MITACS and of associating with
Amazon but having had the taste of a
research internship after the sopho-
more year, I chose to go for the latter.
The beginning: I worked as an intern
in the Amazon Development Center
at Hyderabad for about two and half
months. The internship started with
preliminaries like introduction to the
various cultures and work ethics of
the company, gifting cool company
t-shirts and tumblers!! I was then
introduced to my team named “Cus-
tomer Returns” which dealt with refund-
ing and exchanging customer
Nikita Garg
orders. After a week or so of and move the templates to the
induction sessions on the vari- Amazon Cloud which would make
ous building tools, frameworks them easily customizable according
etc that are used at Amazon, my to the various marketplaces that
mentor introduced me to the Amazon currently serves.
project I was to work on. After some grueling research of what
exactly the current daemons did, I
The project: My team sent vari- realized that these were in every
ous kinds of emails to the cus- sense true to their name “daemons”!!
tomers at various stages of the return My team gave me full liberty to
processing. The email processing was explore into choosing any angle to
being handled by various daemons approach my project from. I talked to
running separately and the email various other teams, especially the
templates that were being populated Amazon cloud team to decide on the
by these daemons were not custom- exact service to store the email tem-
izable without deployment. The pro- plates from the many cloud storage
ject was to integrate the various dae- services that were available.
mons into a single emailing service
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