Pa - Rank

Dear Kunal,

I copied from the attachment sent to you earlier , the following email re Pa-Rank

regards,

hemen

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Google calls it PageRank – to decide the importance of a web page – then use this number to decide the rank ( position ) of that page within the search results

Let us follow Google ( very safe ! )

And call our “ Ranking Mechanism “ of any given resume , a “ Pa-Rank “

Then arrange all arriving resumes ( in the mailbox of a Recruiter or on our web site ), in the descending order of their Pa-Rank

Highest ranked at the top

So , the Recruiter need to open/read only the top 5 / 7

In much the same manner that 95% of the searchers never go beyond the first 3 pages of any search-result despite millions of pages

Just imagine how much time it will save the recruiters to zero-in on the best candidates from amongst hundreds applying for any given job

This has the potential to revolutionize the On-line recruitment industry !

How can we determine a candidate’s Pa-Rank ?

Just like PageRank , which takes into account,

Ø No of Incoming links to a given page

Ø Importance of each incoming link ( based on its own incoming links )

No doubt , Google’s actual algorithm must be very complex – and continues to evolve

Thru Resume Blaster ( and someday , thru My Jobs as well ), we pick-up the “ Contact List “ ( of mobile nos ) of say, Ajay ( a user registered on our site )

These are his “ Primary Incoming Links “ – say , 40

Out of these 40 , say , 10 have also registered on our site AND , are using Resume Blaster

In turn , these 10 have , between them , 600 contacts ( “ Secondary Incoming Links “ )

So , for Ajay , total Incoming links = 40+600 = 640

Now , if Ajay thinks he has figured out how our software computes Pa-Rank then he will somehow find out the mobile number of Mukesh Ambani , and add into his “ Contacts “ – assuming that at one stroke ,he can add ONE MILLION incoming links to himself !

But , we know that such high-flying executives are unlikely to have registered on our site – much less , to be using Resume Blaster !

Hence we treat this as a “ Dead Incoming Link “

On top of that , we can further refine our Pa-Rank based on,

Ø The frequency with which Ajay keeps calling each of those 10 persons ( who have registered on our site AND are also using Resume Blaster )

Ø The duration of each call ( or even text message ? )

We can multiply / sum-up / find average etc of such “ exchanges of messages – both ways “ and arrive at some “ FACTOR “

Then multiply the Total No of Live Incoming Links with this factor , to compute PaRank

Looks crude , no doubt !

But Google has proved that it works !

What PageRank is for all the web pages in the World , someday , PaRank will be to all the resumes ( which too , like any web page , are documents ) , in India

We must do it !

On internet , “ Ideas are dime-a-dozen “

But elegant executions are rare !

Regards

hemen

hemen  parekh

www.hemenparekh.in

Marol , Mumbai , India

hcp@RecruitGuru.com

( M ) +91 - 98,67,55,08,08