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matrix magazine pages

  1. 1. Indian Institute of Technology Guwahati A nd 2 Editionsee inside 1 $ 3 2dimension php security infinity pagerank chomp
  2. 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. 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.x
  4. 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 servicex