Rohit / Akshay :
I picked up from your web site , following
descriptions of your PATENT applications
It is too complicated for me to make sense !
But, I have no doubt that , in the long term , your
inventions will bring about a fundamental change in methods of selecting /
appraising candidates
But , for immediate / short-term benefit ( mostly for
headhunting firms ) , consider the following :
·
These firms are
mandated to find suitable / competent executives from over 50+ diverse
INDUSTRIES ( each , with its own unique requirements of “ Skills and Technology
Knowledge “ on part of the potential candidates
·
Mandates cover
sourcing of talent from 40 + diverse “ FUNCTIONAL “ areas ( again , each having
its own unique requirements of “ EXPERTISE and PROCESS knowledges “
·
Whereas very large
Headhunting Firms , may have recruiters ( consultants ) , specializing either
in a given INDUSTRY or a given FUNCTION , 99 % of the headhunting firms , just
do NOT have the recruiters capable of judging candidates ( especially , in
technical knowledge ), covering such a vast canvass !
·
In fact , these
firms are simply , incapable of shortlisting suitable candidates , purely based
on their TECHNOLOGICAL prowess !
Given this background , what would greatly help ( not
only the recruiters of the headhunting firms but also the interviewers of the
Employer firms ) , is :
# Keywords in resumes ( skills / technology /
expertise / domain knowledge etc ) , get highlighted ( in RED ) and become “
Clickable “
# Clicking on a keyword reveals the
relevant page from Wikipedia ( and many similar sites , providing definitions /
explanations ) . This will help the Recruiters in asking appropriate questions
We had implemented this in www.IndiaRecruiter.net
In fact , we had gone one step ahead and compiled some
15,000 + interview questions which popped up (one relevant to the keyword
clicked )
All of this is fairly simple to implement ( 10 years
ago , it was done by fresh graduates ! )
Of course , none of this is “ patentable “ !
But it will greatly help the recruiters to reach a
better decision while interviewing candidates
You may want to make this an integral feature of
Careerletics
============================
The present disclosure describes method and system for
generating visualized information. The system enables forming a data pool for
career-related information, collected from one or more sources comprising at
least one of candidate resumes, career & company websites, job portals,
online assessment portals, professional networking platforms, social media
platforms and a combination thereof. The system further analyses unstructured
data and transforms it into a format readable by a computer. The system comprises
a machine learning based algorithm wherein processed information is translated
into a career tree, based on similar attributes present in background of other
users. Further, the algorithm detects one or more missing data points and
triggers user-specific survey questions on the interaction platform. The system
provides a comprehensive data platform with all possible deviations to certain
career path, based on career path data collected from multiple users.
A system and method for predicting a personality and
generating a behavioural profile of at least one human subject is disclosed.
The system and method enables capturing of data associated with at least one
human subject or object from one or more sources. The system and method
transforms data into structured data and processes the structured data in order
to generate one or more data variables and one or more data metrics. The system
and method predicts at least one of the personality traits associated with the
at least one human subject or object based upon analysis of the one or more
data variables and the one or more metrics. The system and method further
generates a behaviour profile of the at least one of the user and the object
based upon the one or more personality traits associated with the at least one
of the user and the object.
The present disclosure described herein, in general, a
system and method for determining fraudulent activities of a user by analysing
a user behaviour profile. The data associated with the human subject or object
is received from one or more sources. An encrypted key is generated, to
identify each user. The processor cleans the data by removing unwanted
characters. The processor transforms a raw data into metrics which are usable
by a modelling algorithm. The data is then fed into a risk propensity module
using a machine learning techniques. The machine learning techniques is capable
of handling large number of data. The processor predicts a propensity
associated with the human subject or object by analysing the data.
==========================================
With Regards,
hemen
parekh
(
M ) +91 - 98,67,55,08,08
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