The document describes a machine learning based approach to analyze the prosocial behavior of employees in an organization. It involves analyzing employee data and attributes of prosocial behavior, such as motivations, competencies, emotions, etc. using machine learning algorithms. The results are then stored in a database. The main objective is to study employee strengths and weaknesses in handling different situations. It aims to revolutionize understanding of prosocial attributes through machine learning.

1. 1
FORM 2
THE PATENTS ACT, 1970
(39 OF 1970)
AND
THE PATENT RULES, 2003
COMPLETE SPECIFICATION
(See section 10 and rule 13)
Title of Invention:
“MACHINE LEARNING BASED APPROACH TO ANALYZE THE PROSOCIAL
BEHAVIOR OF EMPLOYEES OF AN ORGANIZATION”
NAME OF APPLICANT NATIONALITY ADDRESS
DR. C. DHANDAPANI INDIAN
PRINCIPAL, RAJAGOPAL POLYTECHNIC
COLLEGE, GUDIYATTAM-632602.
DR. A. SHARMILA INDIAN
ASSOCIATE PROFESSOR, SCHOOL OF
COMMERCE, JAIN (DEEMED-TO-BE
UNIVERSITY) 44/4, DISTRICT FUND
ROAD, JAYANAGAR 9TH BLOCK,
BANGALORE- 560009
DR.S.MURALLIDHAR INDIAN
ASSOCIATE PROFESSOR/ SCHOOL OF
COMMERCE, JAIN DEEMED TO BE
UNIVERSITY, BENGALURU, 560069
EZAZ ABDULSATTAR SHAIKH INDIAN
ASSISTANT PROFESSOR, DEPARTMENT
OF PSYCHOLOGY RADHABAI KALE
MAHILA MAHAVIDYALAYA,
AHMEDNAGAR
KARTHIKAYANI.K INDIAN CHENNAI
DR. ABHISHEK INDIAN
ASSISTANT PROFESSOR, BABA
MASTNATH UNIVERSITY,ROHTAK
124021
N.R.NARESH INDIAN
ASSISTANT PROFESSOR, SCHOOL OF
COMMERCE, JAIN (DEEMED-TO-BE
UNIVERSITY) JAYANAGAR 9TH BLOCK
BENGALURU 560069
DR. RAVINDRA KUMAR INDIAN
FACULTY OF LIBERAL ARTS, ICFAI
UNIVERSITY, TRIPURA 799210
DR.P.ARULPRAKASH INDIAN
ASSOCIATE PROFESSOR & HEAD,
DEPARTMENT OF CSE, RATHINAM
TECHNICAL CAMPUS,
MUGANDA MUNIR MANINI KENYAN
SENIOR LECTURER/DEPARTMENT OF
ECONOMICS, FINANCE AND
ACCOUNTING/KIBABII UNIVERSITY/
BUNGOMA/ 1699-50200
MRS SHYAMALI DAS INDIA
PHD SCHOLAR AT SILICON INSTITUTE
OF TECHNOLOGY IN
BHUBANESWAR,ODISHA
DR THIMMAIAH BAYAVANDA
CHINNAPPA
INDIAN
DEPARTMENT OF MANAGEMENT
STUDIES , IVANE JAVANKISHI TBILISI
STATE UNIVERSITY OF GEORGIA
The following specification describes the invention and the manner in which it is to be
performed.

2. 2
FIELD OF INVENTION
The present invention relates to the field of designing & implementing a framework of
Machine Learning approach to analyze the prosocial behaviour of employees. The
employees of an organization are studied for their strength and weaknesses.
BACKGROUND OF INVENTION
[0001] Background description includes information that may be useful in
understanding the present invention. It is not an admission that any of the
information provided herein is prior art or relevant to the presently claimed
invention, or that any publication specifically or implicitly referenced is prior art.
[0002] Prosocial behaviour is defined as behaviour through which people benefit
others including helping, cooperating, comforting, sharing and donating. Obeying
the rules and conforming to socially accepted behaviours are also regarded as
prosocial behaviour. Prosocial behaviour fosters positive traits that benefits
employees of an organization.
[0003] A number of different types of employee assessment systems that are known
in the prior art. For example, the following patents are provided for their supportive
teachings and are all incorporated by reference.
[0004] US20050267850A1 A method for using machine learning to solve problems
having either a “positive” result (the event occurred) or a “negative” result (the event
did not occur), in which the probability of a positive result is very low and the
consequences of the positive result are significant. Training data is obtained and a
subset of that data is distilled for application to a machine learning system. The
training data includes some records corresponding to the positive result, some
nearest neighbours from the records corresponding to the negative result, and some
other records corresponding to the negative result. The machine learning system

3. 3
uses a co-evolution approach to obtain a rule set for predicting results after a number
of cycles. The machine system uses a fitness function derived for use with the type
of problem, such as a fitness function based on the sensitivity and positive predictive
value of the rules. The rules are validated using the entire set of training data.
[0005] Prosocial behaviours at work can be considered a key element of
organizational effectiveness in the sense that they lead to improvement in the work
environment through a series of acts performed by employees. The proposed
invention focuses on analyzing the impact of prosocial behaviour attributes on
employees of an organization. The algorithms of ML are used to identify the data
sets for strengths and weakness of employees of an organization.
[0006] Above information is presented as background information only to assist
with an understanding of the present disclosure. No determination has been made,
no assertion is made, and as to whether any of the above might be applicable as prior
art with regard to the present invention.
[0007] In the view of the foregoing disadvantages inherent in the known types of
employee analysis systems now present in the prior art, the present invention
provides an improved system. As such, the general purpose of the present invention,
which will be described subsequently in greater detail, is to provide a new and
improved system to analyze prosocial behavioral aspects of the employees of an
organization using machine learning algorithms that has all the advantages of the
prior art and none of the disadvantages.
SUMMARY OF INVENTION
[0008] In the view of the foregoing disadvantages inherent in the known types of
prosocial behavior systems now present in the prior art, the present invention
provides an improved one. As such, the general purpose of the present invention,

4. 4
which will be described subsequently in greater detail, is to provide a new and
improved system that implements the algorithms of prosocial behavior model which
has all the advantages of the prior art and none of the disadvantages.
[0009] The Main objective of the proposed invention is to design & implement a
framework of machine learning to analyze the prosocial behaviour of employees of
an organization. The invention aims at studying the strengths and weakness of
employees of an organization in handling emotions and various situations.
[0010] Yet another important aspect of the proposed invention is to design a
framework where the attributes of prosocial behaviour of an organization is
analyzed. The database of each and every employee is studied along with prosocial
behaviour along with attributes of prosocial behaviour to identify the traits of
employees in various situations such as motivation, competencies, emotions, etc.
The proposed invention will revolutionize the prosocial attributes through machine
learning algorithms.
[0011] In this respect, before explaining at least one embodiment of the invention in
detail, it is to be understood that the invention is not limited in its application to the
details of construction and to the arrangements of the components set forth in the
following description or illustrated in the various ways. Also, it is to be understood
that the phraseology and terminology employed herein are for the purpose of
description and should not be regarded as limiting.
[0012] These together with other objects of the invention, along with the various
features of novelty which characterize the invention, are pointed out with
particularity in the disclosure. For a better understanding of the invention, its
operating advantages and the specific objects attained by its uses, reference should
be had to the accompanying drawings and descriptive matter in which there are

5. 5
illustrated preferred embodiments of the invention.
BREIF DESCRIPTION OF DRAWINGS
[0013] The invention will be better understood and objects other than those set forth
above will become apparent when consideration is given to the following detailed
description thereof. Such description makes reference to the annexed drawings
wherein:
Figure 1 illustrates the block diagram of Machine Learning based approach to
analyze the Prosocial Behaviour of Employees of an Organization, according to the
embodiment herein.
DETAILED DESCRIPTION OF INVENTION
[0014] In the following detailed description, reference is made to the accompanying
drawings which form a part hereof, and in which is shown by way of illustration
specific embodiments in which the invention may be practiced. These embodiments
are described in sufficient detail to enable those skilled in the art to practice the
invention, and it is to be understood that the embodiments may be combined, or that
other embodiments may be utilized and that structural and logical changes may be
made without departing from the spirit and scope of the present invention. The
following detailed description is, therefore, not to be taken in a limiting sense, and
the scope of the present invention is defined by the appended claims and their
equivalents.
[0015] While the present invention is described herein by way of example using
several embodiments and illustrative drawings, those skilled in the art will recognize
that the invention is neither intended to be limited to the embodiments of drawing or
drawings described, nor intended to represent the scale of the various components.
Further, some components that may form a part of the invention may not be

6. 6
illustrated in certain figures, for ease of illustration, and such omissions do not limit
the embodiments outlined in any way. It should be understood that the drawings and
detailed description thereto are not intended to limit the invention to the particular
form disclosed, but on the contrary, the invention covers all modification/s,
equivalents and alternatives falling within the spirit and scope of the present
invention as defined by the appended claims. The headings are used for
organizational purposes only and are not meant to limit the scope of the description
or the claims. As used throughout this description, the word "may" be used in a
permissive sense (i.e., meaning having the potential to), rather than the mandatory
sense (i.e., meaning must). Further, the words "a" or "a" mean "at least one” and the
word “plurality” means one or more, unless otherwise mentioned. Furthermore, the
terminology and phraseology used herein is solely used for descriptive purposes and
should not be construed as limiting in scope. Language such as "including,"
"comprising," "having," "containing," or "involving," and variations thereof, is
intended to be broad and encompass the subject matter listed thereafter, equivalents,
and any additional subject matter not recited, and is not intended to exclude any
other additives, components, integers or steps. Likewise, the term "comprising" is
considered synonymous with the terms "including" or "containing" for applicable
legal purposes. Any discussion of documents, acts, materials, devices, articles and
the like are included in the specification solely for the purpose of providing a
context for the present invention.
[0016] In this disclosure, whenever an element or a group of elements is preceded
with the transitional phrase "comprising", it is understood that we also contemplate
the same element or group of elements with transitional phrases "consisting
essentially of, "consisting", "selected from the group consisting of”, "including", or

7. 7
"is" preceding the recitation of the element or group of elements and vice versa.
[0017] Prosocial behaviours are those intended to help other people. Behaviours that
can be described as prosocial include feeling empathy and concern for others. These
actions are characterized by a concern for the rights, feelings and welfare of other
people.
[0018] There are various situational and social factors that can influence prosocial
behaviours include the interpretation of others needs, the relationship to others, the
reciprocal altruism, the number of bystanders, the normative pressure to help and the
evaluation of the cost to help. The proposed invention focuses on analyzing the
social behaviour aspects of employees of an organization. The invention is to
understand the positive and negative traits of an organization.
[0019] Reference will now be made in detail to the exemplary embodiment of the
present disclosure. Before describing the detailed embodiments that are in
accordance with the present disclosure, it should be observed that the embodiment
resides primarily in combinations arrangement of the system according to an
embodiment herein and as exemplified in FIG. 1
[0020] Figure 1 illustrates the block diagram of Machine Learning based approach
to analyze the Prosocial Behaviour of Employees of an Organization 100. The
proposed system 100 includes a prosocial behaviour analysis unit 101 which include
attributes of 102, 102, 104 and 105 that represents motivations, competencies,
outputs and emotions. The attributes 102, 103, 104 and 105 are analysed along with
database of employees 109a, 109b and 109c. The data sets are fed in to machine
learning unit 107 for clustering and prediction. The results of prediction algorithm
107 are stored on Data base 108.
[0021] In the following description, for the purpose of explanation, numerous

8. 8
specific details are set forth in order to provide a thorough understanding of the
arrangement of the system according to an embodiment herein. It will be apparent,
however, to one skilled in the art that the present embodiment can be practiced
without these specific details. In other instances, structures are shown in block
diagram form only in order to avoid obscuring the present invention.
Gowthami S
Patent Agent
INPA 3797
On behalf of Applicant
Digitally Signed
Date: 28/05/2022

9. 9
WE CLAIM
1. Machine Learning based approach to analyze the Prosocial Behaviour of Employees
of an Organization comprises of
Behaviour analysis unit;
Machine learning unit and
Resultant unit.
2. Machine Learning based approach to analyze the Prosocial Behaviour of Employees
of an Organization, according to claim 1, includes a behaviour analysis unit,
wherein the behaviour analysis unit will analyse the behaviour of employees against
the attributes of prosocial behaviour.
3. Machine Learning based approach to analyze the Prosocial Behaviour of Employees
of an Organization, according to claim 1, includes a machine learning unit, wherein
the machine learning unit will analyse the data sets of behavioural unit and
prosocial attributes.
4. Machine Learning based approach to analyze the Prosocial Behaviour of Employees
of an Organization, according to claim 1, includes a resultant unit, wherein the
resultant unit will analyse the results of predictive unit.
Gowthami S
Patent Agent
INPA 3797
On behalf of Applicant
Digitally Signed
Date: 28/05/2022

10. 10
ABSTRACT
MACHINE LEARNING BASED APPROACH TO ANALYZE THE PROSOCIAL
BEHAVIOUR OF EMPLOYEES OF AN ORGANIZATION
Machine Learning based approach to analyze the Prosocial Behaviour of Employees of an
Organization is the proposed invention. The invention aims at analyzing the impact of
prosocial behaviours and its attributes on employees of an organization. The invention
implements algorithms of machine learning to analyze the strengths and weakness of
employees of an organization.
Gowthami S
Patent Agent
INPA 3797
On behalf of Applicant
Digitally Signed
Date: 28/05/2022