FIELD OF INVENTION:
The present invention relates to the field of electronic communication system. More particularly
the present invention locates the expert as per actions of the user being granted the status of an
'Expert User' andor other users on the system, such as user polling (votes given to) the user
being granted the status of an 'Expert User' (or votes on content created by the user, being
granted the status of an 'Expert User'); accessing or creating content; time spent on the system;
users following the user; being granted the status of an 'Expert User' on the system;
testimonials posted by users for the user, being granted the status of an 'Expert User'; or on the
basis of answers provided by the user, being granted the status of an 'Expert User' to problems
shared by other users on the system The area of expertise of the 'Expert User' is also identified
through the system.
PRIOR ART:
There are currently KMS solutions that provide some form of expert location for example, the
AskMe solution provided by Realcom (http://www.realcom-inc.com/product/h)a s an expert
locator. AskMe uses collaboration to identifj experts for particular areas of knowledge,
implementing expert profiles to manage human sources of area-specific knowledge. These
profiles can be updated dynamically by the experts themselves or may be automatically updated
through processes which monitor information published by the expert. However, such a system
does not determine the domain of expertise of an 'expert' identified.
Also some knowledge corroboration involves trying to exploit the "wisdom of the crowds" by
using knowledge from many different people, organizations, committees, enterprises, automated
systems or other entities. For example, a majority voting system is one example of knowledge
corroboration where many people vote on an issue and the majority vote is used as the outcome.
Knowledge corroboration is difficult where the knowledge of the individuals to be corroborated
is poor or very variable and where some individuals may act maliciously by reporting false
information on purpose. In addition, in order to exploit knowledge corroboration, large scale
systems are needed in order to corroborate knowledge from large numbers of entities. Providing
knowledge corroboration solutions which are efficient and which scale up for use with huge
amounts of data is difficult.
Reference may be made to the following:
-3-
US publication no 201 10161 129 relates to a method for locating experts which includes
receiving a first query from a first user requesting the identity of persons having desired skills.
The names of persons in a database having the desired skills are then identified. A second query
is sent to a plurality of additional users requesting the verification of the information relating to
the skills of the identified persons. Responses from the plurality of users are used to amend the
information relating to skills of the identified persons. While this patent talks about how
expertise can be verified, it doesn't talk about how an 'expert user' and his domain of expertise is
identified.
Publication No. 20120150771 relates to the probabilistic learning system having a graphical
assessment component which aggregates the answers in a manner which takes into account the
learnt expertise in order to determine enhanced answers. This system, however does not talk
about how 'expert users' and their domain of expertise can be identified. Furthermore, the
method outlined in this publication is only question-answer based and the domain of expertise in
the method outlined in this publication is already identified-it does not talk about how the
domain of expertise is identified.
Publication No. US2003195787 relates to system, method, and software product for
distributing expert advice to an advice-seeker while on location at their selected activity. The
system, method, and software product allow a user to use a variety of devices, including phones,
handheld computers, and desktop computers, to quickly and cheaply connect
to expertinformation while on location at their selected activity. While this system only refers to
how expert information can be distributed over a communications network, it does not try to
identify experts on the basis of actions on documents or items created within a given topical area.
Publication No. 20050131897 relates to system and method of the invention analyzes activities
of users in a recommender system to identify experts. Two types of experts may be identified:
authoritative experts and hub experts. An authoritative experts is a user who creates items or
documents in a given field that are acted upon by a large number of users within a community
who are well connected in the given field. A hub expert is a user who is aware of important items
or documents within a given field and uses, works or acts upon items or documents produced by
authoritative experts. This system talks about how expert advice can be distributed over a
communications network.
-4-
Publication No. 20030140037 relates to a method of generating a search result list of experts
substantially in real-time in response to a search request from a user using a computer network,
involving maintaining an updateable and searchable database of expert profiles wherein attributes
of an expert are stored within the profiles, receiving a search request from the user, and applying
a weight designated by the user to attributes of the expert.
Publication No. WOO135272 relates to routing computer users seeking expert help to experts in
one or more topic areas in an online setting. This system doesn't talk about how 'expert users'
and their domain of expertise can be identified from within a given set of users. This publication
also talks about only about a network of computers.
Publication No. 20120226521 relates to identifjling experts and influencers in a social network
and utilizing the identified experts and influencers for advertising, social grouping, and other
suitable purposes. Particular embodiments access one or more experts and one or more
influencers identified for a subject matter, wherein the one or more experts and the one or more
influencers are among one or more users of a social-networking system; and invite a first expert
and a second expert to establish a first social connection within the social-networking system.
This publication does not talk about how 'expert users' and their domain of expertise are
identified, but instead how already identified experts can be invited to a social network.
Publication No. 20080183759 relates to a computer-assisted method for identifling, from among
a group of patent practitioners in a specified locale, one or more practitioners having technical
expertise related to a given invention or area of technology. The publication talks only about
identification of domain of expertise, from within an already identified set of practitioners, (but
not of the 'experts' themselves). Furthermore, this publication is limited to the domain of patent
practitioners.
Publication No. 20120254095 relates to computer-implemented expertise discovery system that
generates recommendations of people in accordance with inferences of levels of expertise from
behavioral information. The publication talks about discovering experts based on behavioral
patterns and the domain is 'specified'.
Patent No. 7,272,597 relates to a system for identifjling an expert domain for a query includes
maintaining a query ontology that includes one or more query categories and one or more queries
I -5-
associated with each of the one or more categories. The one or more queries associated with a
I
particular category included in the query ontology represent queries associated with that
I particular category. Search results are retrieved for queries included in the query ontology. This
publication restricts itself for identifying expert domains from within a topical area only, and not
on identifjling expert users and their domain of expertise.
US publication no 20100205541 relates to the machine-implemented social networking system
builds up and repeatedly refreshes a hierarchy tree containing topic nodes. This method is to help 1 people identifL relevant conversations and be a part of them based on their interests and current
conversations. These users may or may not be part of a real time chat environment, which is what
this publication talks about. Also the technology in this suggests people different chat rooms,
based on their interest area. This system talks about how users can be grouped on the basis of
interest areas which is not the same as 'expertise arealdomain'. Also, in the current publication,
users are not given enhanced privileges on the system, they are just matched on the basis of
interest areas.
Reference may be made to an article entitled "The Innovative Use of Mobile Applications in East
Africa " by "Johan Hellstrom, 2010 ". The article talks about mobile devices can, under the right
conditions, have a broad positive effect on agricultural markets in general by facilitating just-intime,
many-to-many information flows that are an increasingly important element in developing
country agricultural markets that are growing more integrated with, and subject to the shifts in,
regional and global markets. Mobile devices and services can also help smallholders, and the
rural poor in general, connect with one another for more effective collective action, both as
producers through cooperatives and producer organisations, and as citizens in demanding
improved, more transparent and responsive governance and public services. They can help
improve advance warning of weather risks, pest and disease outbreaks, and other environmental
risks, and provide timely, locally-relevant information on how to respond to these. In this book
author has imagined a scenario of using voting on mobile to conduct local elections.
Reference may be made to an article entitled "A quantitative approach to identifiing
expertise "by Avaya Labs Research, USA, Bell Laboratories, USA, CSE, 2002. The article talks
about a tool that uses data from change management systems to locate people with desired
expertise. It uses a quantification of experience, and presents evidence to validate this
quantification as a measure of expertise. This publication talks about using data from change
management systems. Furthermore, this publication restricts itself to the domain of technology
and software development.
Reference may be made to an article entitled "A survey of algorithms and systems for expert
location in social network"by University of California Riverside, California, USA, Yahoo! Labs,
Santa Clara, USA, Boston University, Boston, USA, Social Network Data Analytics, pp 215-
24 1 , 201 1. The article talks about algorithms that identify effective expert teams within a
network of experts. This publication talks about assessing the level of expertise from within an
already identified set of experts, whereas the proposed invention doesn't look at ascertaining
I level of expertise. Instead, the proposed invention looks at how a set of 'expert users' and their
domain of expertise can be identified from a given set of users.
Thus the conventional systems disclose peer to peer based collective filtering for locating experts
as per the voting by the user. None of the systems talk about the reversability of the vote. None
of the system provides method on how 'expert users' and their domain of expertise can be
identified on the basis of multiple criteria and how 'expert information sources' can be identified
in the form of expert users from within a given set of users.
Hence there exists a need for an improved system and method of generating content and create
engagement for the other users in the system with only limited number of expert users in the
system at any given point in time for a given number of users.
Also, none of the systems can be used across domains and not limited to the domain of expertise.
Thus in view of the above prior art, the present invention provides a system and method for
locating expert based on user polling. The system allows any user to generate content and create
engagement for other users in the system. The system has users selecting experts directly through
voting, and not based on automatic processes. Moreover, the present invention can be used across
domains, and is not limited to the domain of patent expertise as in the prior arts disclosed.
OBJECTS OF THE INVENTION
Primary object of the present invention is to provide a system and method to identify expert users
and their area of expertise through the system.
Another object of the present invention is to provide a system and method, which allows any user
to generate content and create engagement for other users in the system.
Yet another object of the present invention is to provide a system and method, which allow users
to access and share content by minimal taps, inputs or number of clicks.
Still another object of the present invention is to provide a system and method having flexibility
to reverse the grant of expert user status on the basis of activities carried out by other users on the
system
Yet another object of the present invention is to provide a system and method for an easy and
cost effective method of identifying an Expert User and having access to expert advice at any
location such as but not limited to rural or urban.
Another object of the present invention is to provide a system and method of locating an expert
which is easy and cost effective.
Another object of the present invention is to provide a platform where all users can participate in
the expert selection process, and where all users can be granted the status of an 'Expert User' on
the basis of activities carried out by the user being granted the status of an 'Expert User' and/or
by people connected to them on the system.
Another object of the present invention is to enable users to vote for any user who is connected to
them on the system, at any given point in time. The system also provides users the flexibility to
withdraw this vote from the user previously voted for, on the system at any given point in time.
Yet another object of the present invention is to enable users to follow expert users or topics of
their interest, to access relevant content on the system.
Another object of the invention is to provide points to users, based on the activities that they
perform. These points can be used to grant the status of an 'expert user', with enhanced
privileges on the system.
I Another object of the present invention is to provide ?users the flexibility to upload testimonials
I for other users on the system, which can be used to determine an 'expert user' from within the
I system.
Another object of the present invention is to enable users to rate content created by other users on
I the system, which can be used to determine the 'expert user'
Yet another object of the present invention is to determine the area of expertise of the expert
user, based on activities performed on the system by the expert user, and/or other users.
SUMMARY
The present invention provides a system and method for identiQing an Expert User based on
actions of the user being granted the status of an 'Expert User' and/or other users on the system,
such as user polling (votes given to) the user being granted the status of an 'Expert User' (or
votes on content created by the user, being granted the status of an 'Expert User'); accessing or
creating content; time spent on the system; users following the user; being granted the status of
an 'Expert User' on the system; testimonials posted by users for the user, being granted the status
of an 'Expert User'; or on the basis of answers provided by the user, being granted the status of
an 'Expert User' to problems shared by other users on the system The area of expertise of the
'Expert User' is also identified through the system. The system and method allows user to access
and share content by minimal taps, inputs or number of clicks.
In a preferred embodiment of the present invention, the present invention provides a system
and method for identifying 'expert users' and their domain of expertise fiom within a given set of
users through multiple criteria which are not limited to behavioral information. The system
comprises of a database, expert identification algorithm and at least a communication device or
hand held communication device comprising communication interface, a processor, main
memory, display unit with interface, secondary memory comprising hard disk drive, removable
storage drive, interface for secondary storage with removable storage units and communication
interface and communication path.
In another embodiment of the present invention, identification of an 'expert user' in the
present invention is on the basis of such as but not limited to votes or testimonials received from
other users, on the basis of rating of the content by-other users, posted in the system by the
'expert user' and wherein no behavioral information is taken into account of the expert user
himselflherself.
In another embodiment of the present invention, the system for identifLing 'expert users' and
their domain of expertise is user-centric and not domain centric.
In another embodiment of the present invention, the system allows users to vote for other
I users whom they are directly connected to on the system.
In another embodiment of the present invention, expert users can be provided enhanced
privileges on the system.
In another embodiment of the present invention, the system doesn't prompt users to be a part
of a certain conversation; the user himself chooses what conversations he would want to be a part
of.
In another embodiment of the present invention, users do not have a position in a network,
and 'expert users' are identified from within the users such that there is no concept of hierarchy
in the network, till an 'expert user' is identified through the use of multiple criteria.
In another embodiment of the present invention, the voting for finding expert in a
communication network is in peers.
In an embodiment, the invention is generic, and can be used across any domain such as but not
limited to agriculture, health etc
BRIEF DESCRIPTION OF THE DRAWING
Further objects and advantages of this invention will be more apparent from the ensuing
description when read in conjunction with the accompanying drawings and wherein:
Figure I shows the block diagram of the system according to the present invention;
Figure 2 shows the block diagram of the architecture according to the present invention;
Figure 3 shows the block diagram of the method followed for identification of "expert user"
according to the present invention;
I DETAILED DESCRIPTION OF THE DRAWINGS:
i The present invention provides a system and method for locating expert based on actions of the
user being granted the status of an 'Expert User' and/or other users on the system through
I multiple criteria. The system comprises of a database, expert identification algorithm and at least
a communication device or hand held communication device Reference may be made to figure 1,
which shows the block digram of the communication device according to the present invention.
The communication device comprises a communication infrastructure 201, a processor 202, main
memory 203, display unit 204 with interface 205, secondary memory 206 comprising hard disk
drive 207, removable storage drive 208 and interface for secondary storage 209, with removable
storage units 210, 21 1, communication interface 21 2 and communication path 213. The user
when uses the application, through the communication device, the profile of user itself and the
content generated by user is available to other users in the network through the application (the
content and interaction gets recorded in the database via the communication device in which
various device components like processor, internal memory etc are used) and other users can also
interact on a user's profile and user's content through the communication devices connected to
the network. The system records all these interactions through different metrics to determine the
expert among the users and their expertise. For example: if a user has created lot of content under
the topics which are linked to agriculture and that content is viewed by lot of users and also the
user itself is voted by other users as an expert, the system can identify the user who has created
the content to be an expert in the domain of agriculture.
Fig. 2 illustrates the architecture of the system according to the present invention for identifLing
expert among a number of users. 'Expert users' are added to the systemlidentified from within
the system through any combination of contact book of other users, social networks, existing
users of the system, through an existing organization, through a directory or through a social
security or national identity equivalent. After identification, the user communicates with the
expert through hand held device. The method comprises user entry into the system, identification
of expert, method of identifying expert and validation. When an expertise and "expert user" is
identified, is granted by some enhanced privileges on the system.
Fig. 3 illustrates the method followed for identifLing expert users and their area of expertise from
within a given set of users through multiple criteria. This criteria includes any combination of
votes received from other users, content accessed, time spent on the system, content created,
answering questions of other users, on the basis of followers or subscribers on the system, (from
within the other users) testimonials received from other users as well as votes received from
-1 1-
Other users on the content created by the expert user. Furthermore, the invention also provides
for enhanced privileges to be granted to the 'expert user' thus identified. Also, users have the
flexibility to un-vote the 'expert user' they have voted for. Therefore, the invention is dynamic,
and users can be elevated to the status of an expert user and expert users can also be downgraded
to the status of a normal user.
The system and method allows user to access and share content by minimal taps, inputs or
number of clicks. Any user can generate content and create engagement for the other users in the
system. Any user can be granted the status of an 'expert user' based on the criteria outline above,
and once an 'expert user' and the user's area of expertise are identified, the user can be upgraded
to have certain privileges, which otherwise are not accessible to normal users. The criteria of
selection of such an expert user can be changed from time to time. These mechanisms allow
users to empower themselves or another peer to have privileges, which allows the Expert User to
further improve his1 her productivity within the system.
In an aspect, the criteria for selection of 'expert users' can keep changing dynamically, based on
the performance of the users on the system.
Thus the present invention is an easy and cost effective method of identifying an expert user and
having access to expert advice at any location such as but not limited to rural or urban.
It is to be noted that the present invention is susceptible to modifications, adaptations and
changes by those skilled in the art. Such variant embodiments employing the concepts and
features of this invention are intended to be within the scope of the present invention, which is
further set forth under the following claims:-

WE CLAIM
I . A system and method to identify expert users and their area of expertise from within a given
set of users through multiple criteria wherein the system comprises of a database, expert
identification algorithm and at least one communication device or hand held communication
device comprising communication interface, a processor, main memory, display unit with
interface, secondary memory further comprising hard disk drive, removable storage drive,
interface for secondary storage with removable storage units and communication interface
and communication path.
2. The system and method to identify expert users and their area of expertise from within a
given set of users as claimed in claim I , wherein criteria for identifying the expert user and
area of expertise is chosen from any combination of the votes given by the other users
through voting in the mobilelweb application network, the activity done such as accessing the
content in the rnobilelweb application network, activity such as time spent in the rnobilelweb
application network, activity such as creating content, activity such as answering questions,
the number of followers or subscribers the user has in the mobilelweb application network,
the number of testimonials the user has received, the number of votes on content created or
shared by the user in the rnobilelweb application network.
3. The system and method to identify expert users-and their area of expertise from within a
given set of users as claimed in claim 1, wherein the method for identifying an expert and
user's expertise comprises the steps of: identifying the user from any combination of the
following ways: selected from the contact book of a user's phone, from the external social
network sites of a user, from the existing users of the mobilelweb application, from a
previously identified organization, from a directory, from a social security number or
equivalent national identity proof; identification of the expert user and area of expertise by
other users; determining the expert user and area of expertise by other users based on one or
more criteria selected from the votes given by the other users through a voting button in the
mobile/web application network, the activity done such as accessing the content in the
mobilelweb application network, activity such as time spent in the mobilelweb application
network, activity such as creating content, activity such as answering questions, the number
of followers or subscribers the user has in the rnobilelweb application network, the number
of testimonials the user has received, the number of votes on content created or shared by the
user in the mobilelweb application network
4. The system and method to identify expert users and their area of expertise from within a
given set of users as claimed in claim 1, wherein the method comprises any of the
combination of ways of identification of user and'criteria for identifying the expert user and
area of expertise.
5. The system and method to identify expert users and their area of expertise fiom within a
given set of users as claimed in claim 1, wherein expert user is provided with enhanced
privileges on the system which otherwise are not accessible to normal users.
6. The system and method to identify expert users and their area of expertise from within a
given set of users as claimed in claim 1, wherein the system doesn't prompt users to be a part
of a certain conversation; the user himself chooses what conversations he would want to be a
part of.
7. The system and method to identify expert users and their area of expertise fiom within a
given set of users as claimed in claim 1, wherein the method enables user to vote for any user
who is connected to them on the system, at any given point in time.
8. The system and method to identify expert users and their area of expertise from within a
given set of users as claimed in claim I, wherein the system provides users the flexibility to
withdraw the vote from the user previously voted for, on the system at any given point in
time.
9. The system and method to identify expert users and their area of expertise from within a
given set of users as claimed in claim 1, wherein the system for identifying 'expert users' and
their domain of expertise is user-centric and not domain centric.
10. The system and method to identify expert users and their area of expertise from within a
given set of users as claimed in claim 1, wherein the area of expertise is identified across any
domain and is not restricted to a particular domain.